Alternatives to Apache Accumulo

Redis Labs is the home of Redis. Redis Enterprise is the best Redis version. Redis Enterprise is more than a cache. Redis Enterprise can be free in the cloud with NoSQL and data caching using the fastest in-memory database. Redis can be scaled, enterprise-grade resilience, massive scaling, ease of administration, and operational simplicity. Redis in the Cloud is a favorite of DevOps. Developers have access to enhanced data structures and a variety modules. This allows them to innovate faster and has a faster time-to-market. CIOs love the security and expert support of Redis, which provides 99.999% uptime. Use relational databases for active-active, geodistribution, conflict distribution, reads/writes in multiple regions to the same data set. Redis Enterprise offers flexible deployment options. Redis Labs is the home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.

Amazon DynamoDB is a versatile key-value and document database that provides exceptional single-digit millisecond performance, regardless of scale. As a fully managed service, it offers multi-region, multimaster durability along with integrated security features, backup and restore capabilities, and in-memory caching designed for internet-scale applications. With the ability to handle over 10 trillion requests daily and support peak loads exceeding 20 million requests per second, it serves a wide range of businesses. Prominent companies like Lyft, Airbnb, and Redfin, alongside major enterprises such as Samsung, Toyota, and Capital One, rely on DynamoDB for their critical operations, leveraging its scalability and performance. This allows organizations to concentrate on fostering innovation without the burden of operational management. You can create an immersive gaming platform that manages player data, session histories, and leaderboards for millions of users simultaneously. Additionally, it facilitates the implementation of design patterns for various applications like shopping carts, workflow engines, inventory management, and customer profiles. DynamoDB is well-equipped to handle high-traffic, large-scale events seamlessly, making it an ideal choice for modern applications.

Utilize Apache HBase™ when you require immediate and random read/write capabilities for your extensive data sets. This initiative aims to manage exceptionally large tables that can contain billions of rows across millions of columns on clusters built from standard hardware. It features automatic failover capabilities between RegionServers to ensure reliability. Additionally, it provides an intuitive Java API for client interaction, along with a Thrift gateway and a RESTful Web service that accommodates various data encoding formats, including XML, Protobuf, and binary. Furthermore, it supports the export of metrics through the Hadoop metrics system, enabling data to be sent to files or Ganglia, as well as via JMX for enhanced monitoring and management. With these features, HBase stands out as a robust solution for handling big data challenges effectively.

FoundationDB operates as a multi-model database, enabling the storage of various data types within a single system. Its Key-Value Store component ensures that all information is securely stored, distributed, and replicated. The installation, scaling, and management of FoundationDB are straightforward, benefiting from a distributed architecture that effectively scales and handles failures while maintaining the behavior of a singular ACID database. It delivers impressive performance on standard hardware, making it capable of managing substantial workloads at a minimal cost. With years of production use, FoundationDB has been reinforced through practical experience and insights gained over time. Additionally, its backup system is unparalleled, utilizing a deterministic simulation engine for testing purposes. We invite you to become an active member of our open-source community, where you can engage in both technical and user discussions on our forums and discover ways to contribute to the project. Your involvement can help shape the future of FoundationDB!

InterSystems IRIS, a cloud-first data platform, is a multi-model transactional database management engine, application development platform, interoperability engine and open analytics platform. InterSystems IRIS offers a variety of APIs that allow you to work with transactional persistent data simultaneously. These include key-value, relational and object, document, and multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS features an Interoperability engine as well as modules for building AI solutions. InterSystems IRIS features horizontal scalability (sharding and ECP), and High Availability features such as Business intelligence, transaction support and backup.

This robust enterprise platform, built on Apache Ignite, delivers lightning-fast in-memory performance and extensive scalability for data-heavy applications, ensuring real-time access across various datastores and applications. Transitioning from Ignite to GridGain requires no code modifications, allowing for secure deployment of clusters on a global scale without experiencing any downtime. You can conduct rolling upgrades on your production clusters without affecting application availability, and replicate data across geographically dispersed data centers to balance workloads and mitigate the risk of outages in specific regions. Your data remains secure both at rest and in transit, while compliance with security and privacy regulations is guaranteed. Seamless integration with your organization’s existing authentication and authorization frameworks is straightforward, and comprehensive auditing of data and user activities can be enabled. Additionally, you can establish automated schedules for both full and incremental backups, ensuring that restoring your cluster to its most stable state is achievable through snapshots and point-in-time recovery. This platform not only promotes efficiency but also enhances resilience and security for all data operations.

When seeking a database that ensures both scalability and high availability without sacrificing performance, Apache Cassandra stands out as an ideal option. Its linear scalability paired with proven fault tolerance on standard hardware or cloud services positions it as an excellent choice for handling mission-critical data effectively. Additionally, Cassandra's superior capability to replicate data across several datacenters not only enhances user experience by reducing latency but also offers reassurance in the event of regional failures. This combination of features makes it a robust solution for organizations that prioritize data resilience and efficiency.

Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads. Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis. Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps. Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.

Store data in its native format for graph, document, and search purposes. Leverage a comprehensive query language that allows for rich access to this data. Map the data directly to the database and interact with it through optimal methods tailored for specific tasks, such as traversals, joins, searches, rankings, geospatial queries, and aggregations. Experience the benefits of polyglot persistence without incurring additional costs. Design, scale, and modify your architectures with ease to accommodate evolving requirements, all while minimizing effort. Merge the adaptability of JSON with advanced semantic search and graph technologies, enabling the extraction of features even from extensive datasets, thereby enhancing data analysis capabilities. This combination opens up new possibilities for handling complex data scenarios efficiently.

ScyllaDB serves as an ideal database solution for applications that demand high performance and minimal latency, catering specifically to data-intensive needs. It empowers teams to fully utilize the growing computing capabilities of modern infrastructures, effectively removing obstacles to scaling as data volumes expand. Distinct from other database systems, ScyllaDB stands out as a distributed NoSQL database that is completely compatible with both Apache Cassandra and Amazon DynamoDB, while incorporating significant architectural innovations that deliver outstanding user experiences at significantly reduced costs. Over 400 transformative companies, including Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung, rely on ScyllaDB to tackle their most challenging database requirements. Furthermore, ScyllaDB is offered in various formats, including a free open-source version, a fully-supported enterprise solution, and a fully managed database-as-a-service (DBaaS) available across multiple cloud platforms, ensuring flexibility for diverse user needs. This versatility makes it an attractive choice for organizations looking to optimize their database performance.

etcd serves as a highly reliable and consistent distributed key-value store, ideal for managing data required by a cluster or distributed system. It effectively manages leader elections amidst network splits and is resilient to machine failures, including those affecting the leader node. Data can be organized in a hierarchical manner, similar to a traditional filesystem, allowing for structured storage. Additionally, it offers the capability to monitor specific keys or directories for changes, enabling real-time reactions to any alterations in values, ensuring that systems stay synchronized and responsive. This functionality is crucial for maintaining consistency across distributed applications.

Aerospike is the global leader for next-generation, real time NoSQL data solutions at any scale. Aerospike helps enterprises overcome seemingly impossible data bottlenecks and compete with other companies at a fraction of the cost and complexity of legacy NoSQL databases. Aerospike's Hybrid Memory Architecture™ is a patented technology that unlocks the full potential of modern hardware and delivers previously unimaginable value. It does this by delivering unimaginable value from huge amounts of data at both the edge, core, and in the cloud. Aerospike empowers customers with the ability to instantly combat fraud, dramatically increase shopping cart sizes, deploy global digital payment networks, and provide instant, one-to-1 personalization for millions. Aerospike customers include Airtel and Banca d'Italia as well as Snap, Verizon Media, Wayfair, PayPal, Snap, Verizon Media, and Nielsen. The company's headquarters is in Mountain View, California. Additional locations are in London, Bengaluru, India, and Tel Aviv in Israel.

Introducing a premier high-performance distributed SQL database that is open source and designed specifically for cloud-native environments, ideal for powering applications on a global internet scale. Experience minimal latency, often in the single-digit milliseconds, allowing you to create incredibly fast cloud applications by executing queries directly from the database itself. Handle immense workloads effortlessly, achieving millions of transactions per second and accommodating several terabytes of data on each node. With geo-distribution capabilities, you can deploy your database across various regions and cloud platforms, utilizing synchronous or multi-master replication for optimal performance. Tailored for modern cloud-native architectures, YugabyteDB accelerates the development, deployment, and management of applications like never before. Enjoy enhanced developer agility by tapping into the full capabilities of PostgreSQL-compatible SQL alongside distributed ACID transactions. Maintain resilient services with assured continuous availability, even amidst failures in compute, storage, or network infrastructure. Scale your resources on demand, easily adding or removing nodes as needed, and eliminate the necessity for over-provisioned clusters. Additionally, benefit from significantly reduced user latency, ensuring a seamless experience for your app users.

LeanXcale is a rapidly scalable database that merges the features of both SQL and NoSQL systems. It is designed to handle large volumes of both batch and real-time data pipelines, ensuring that this data is accessible through SQL or GIS for diverse applications, including operational tasks, analytics, dashboard creation, or machine learning processes. Regardless of the technology stack in use, LeanXcale offers users the flexibility of SQL and NoSQL interfaces. The KiVi storage engine functions as a relational key-value data repository, enabling data access not only via the conventional SQL API but also through a direct ACID-compliant key-value interface. This particular interface facilitates high-speed data ingestion, optimizing efficiency by eliminating the overhead associated with SQL processing. Furthermore, its highly scalable and distributed storage engine spreads data across the cluster, thereby enhancing both performance and reliability while accommodating growing data needs seamlessly.

In-Memory Computing Platform. Digital world is different. Microseconds are important. The world's most important organizations rely on us for powering their most sensitive applications at scale. If they meet the current requirement for immediate access, new data-enabled apps can transform your business. Hazelcast solutions can be used to complement any database and deliver results that are much faster than traditional systems of record. Hazelcast's distributed architecture ensures redundancy and continuous cluster up-time, as well as always available data to support the most demanding applications. The capacity grows with demand without compromising performance and availability. The cloud delivers the fastest in-memory data grid and third-generation high speed event processing.

JanusGraph stands out as a highly scalable graph database designed for efficiently storing and querying extensive graphs that can comprise hundreds of billions of vertices and edges, all managed across a cluster of multiple machines. This project, which operates under The Linux Foundation, boasts contributions from notable organizations such as Expero, Google, GRAKN.AI, Hortonworks, IBM, and Amazon. It offers both elastic and linear scalability to accommodate an expanding data set and user community. Key features include robust data distribution and replication methods to enhance performance and ensure fault tolerance. Additionally, JanusGraph supports multi-datacenter high availability and provides hot backups for data security. All these capabilities are available without any associated costs, eliminating the necessity for purchasing commercial licenses, as it is entirely open source and governed by the Apache 2 license. Furthermore, JanusGraph functions as a transactional database capable of handling thousands of simultaneous users performing complex graph traversals in real time. It ensures support for both ACID properties and eventual consistency, catering to various operational needs. Beyond online transactional processing (OLTP), JanusGraph also facilitates global graph analytics (OLAP) through its integration with Apache Spark, making it a versatile tool for data analysis and visualization. This combination of features makes JanusGraph a powerful choice for organizations looking to leverage graph data effectively.

Utilize Ignite as a conventional SQL database by employing JDBC drivers, ODBC drivers, or the dedicated SQL APIs that cater to Java, C#, C++, Python, and various other programming languages. Effortlessly perform operations such as joining, grouping, aggregating, and ordering your distributed data, whether it is stored in memory or on disk. By integrating Ignite as an in-memory cache or data grid across multiple external databases, you can enhance the performance of your existing applications by a factor of 100. Envision a cache that allows for SQL querying, transactional operations, and computational tasks. Develop contemporary applications capable of handling both transactional and analytical workloads by leveraging Ignite as a scalable database that exceeds the limits of available memory. Ignite smartly allocates memory for frequently accessed data and resorts to disk storage when dealing with less frequently accessed records. This allows for the execution of kilobyte-sized custom code across vast petabytes of data. Transform your Ignite database into a distributed supercomputer, optimized for rapid calculations, intricate analytics, and machine learning tasks, ensuring that your applications remain responsive and efficient even under heavy loads. Embrace the potential of Ignite to revolutionize your data processing capabilities and drive innovation within your projects.

Azure Cosmos DB offers a fully managed NoSQL database solution tailored for contemporary application development, ensuring single-digit millisecond response times and an impressive availability rate of 99.999 percent, all supported by service level agreements. This service provides automatic, instantaneous scalability and supports open-source APIs for MongoDB and Cassandra, allowing for rapid data operations. With its turnkey multi-master global distribution, users can experience swift read and write operations from any location around the globe. Additionally, Azure Cosmos DB enables organizations to accelerate their decision-making processes by facilitating near-real-time analytics and AI capabilities on the operational data housed within the database. Furthermore, Azure Synapse Link for Azure Cosmos DB integrates effortlessly with Azure Synapse Analytics, ensuring smooth performance without necessitating data movement or compromising the efficiency of the operational data store, enhancing the overall functionality of your data strategy. This integration not only streamlines workflows but also empowers users to derive insights more efficiently.

LevelDB is a high-performance key-value storage library developed by Google, designed to maintain an ordered mapping between string keys and string values. The keys and values are treated as arbitrary byte arrays, and the stored data is organized in a sorted manner based on the keys. Users have the option to supply a custom comparison function to modify the default sorting behavior. The library allows for multiple changes to be grouped into a single atomic batch, ensuring data integrity during updates. Additionally, users can create a temporary snapshot for a consistent view of the data at any given moment. The library supports both forward and backward iteration through the stored data, enhancing flexibility during data access. Data is automatically compressed using the Snappy compression algorithm to optimize storage efficiency. Moreover, interactions with the external environment, such as file system operations, are managed through a virtual interface, giving users the ability to customize how the library interacts with the operating system. In practical applications, we utilize a database containing one million entries, where each entry consists of a 16-byte key and a 100-byte value. Notably, the values used in benchmarking compress to approximately half of their original size, allowing for significant space savings. We provide detailed performance metrics for sequential reads in both forward and reverse directions, as well as the effectiveness of random lookups, to showcase the library's capabilities. This comprehensive performance analysis aids developers in understanding how to optimize their use of LevelDB in various applications.

RocksDB is a high-performance database engine that employs a log-structured design and is entirely implemented in C++. It treats keys and values as byte streams of arbitrary sizes, allowing for flexibility in data representation. Specifically designed for rapid, low-latency storage solutions such as flash memory and high-speed disks, RocksDB capitalizes on the impressive read and write speeds provided by these technologies. The database supports a range of fundamental operations, from basic tasks like opening and closing a database to more complex functions such as merging and applying compaction filters. Its versatility makes RocksDB suitable for various workloads, including database storage engines like MyRocks as well as application data caching and embedded systems. This adaptability ensures that developers can rely on RocksDB for a wide spectrum of data management needs in different environments.

OrbitDB functions as a decentralized, serverless, peer-to-peer database that leverages IPFS for data storage and utilizes Libp2p Pubsub for seamless synchronization among peers. It incorporates Merkle-CRDTs to facilitate conflict-free writing and merging of database entries, making it ideal for decentralized applications, blockchain projects, and web apps designed to operate primarily offline. The platform provides a range of database types that cater to distinct requirements: 'events' serves as immutable append-only logs, 'documents' allows for JSON document storage indexed by specific keys, 'keyvalue' offers conventional key-value pair storage, and 'keyvalue-indexed' provides LevelDB-indexed key-value data. Each of these database types is constructed on OpLog, a structure that is immutable, cryptographically verifiable, and based on operation-driven CRDT principles. The JavaScript implementation is compatible with both browser and Node.js environments, while a version in Go is actively maintained by the Berty project, ensuring a wide range of support for developers. This flexibility and adaptability make OrbitDB a powerful choice for those looking to implement modern data solutions in distributed systems.

HerdDB is a distributed SQL database developed in Java, making it embeddable within any Java Virtual Machine. It has been specifically optimized for rapid write operations and efficient access patterns for primary key read and updates. Capable of managing numerous tables, HerdDB allows for straightforward addition and removal of hosts as well as flexible reconfiguration of tablespaces to effectively balance loads across multiple systems. Utilizing Apache Zookeeper and Apache Bookkeeper, HerdDB achieves a fully replicated architecture that eliminates any single point of failure. At its core, HerdDB shares similarities with key-value NoSQL databases, but it also incorporates an SQL abstraction layer along with JDBC Driver support, allowing users to easily transition existing applications to its platform. Additionally, at Diennea, we have created EmailSuccess, a highly efficient Mail Transfer Agent designed to deliver millions of emails per hour to recipients worldwide, showcasing the capabilities of our technology. This seamless integration of advanced database management and email delivery systems reflects our commitment to providing powerful solutions for modern data handling.

Introducing Speedb, the cutting-edge key-value storage engine that is fully compatible with RocksDB, offering enhanced stability, efficiency, and performance improvements. By becoming a part of the Hive, Speedb’s open-source community, you can engage with others to refine and exchange insights and best practices regarding RocksDB. Speedb stands as a viable alternative for users of LevelDB and RocksDB who are looking to elevate their applications. If you are utilizing event streaming platforms such as Kafka, Flink, Spark, Splunk, or Elastic, incorporating Speedb can significantly boost their performance. The growing volume of metadata in contemporary data sets is leading to notable performance challenges for various applications, but with Speedb, you can maintain affordable costs while ensuring your applications run seamlessly, even during peak demand. When considering whether to upgrade or implement a new key-value store within your infrastructure, Speedb is well-equipped to meet the demands. By integrating Speedb's sophisticated key-value storage engine into your projects, you will swiftly notice enhancements in performance and efficiency, allowing you to focus on innovation rather than troubleshooting.

Infinispan is an open-source, in-memory data grid that provides versatile deployment possibilities and powerful functionalities for data storage, management, and processing. This technology features a key/value data repository capable of accommodating various data types, ranging from Java objects to simple text. Infinispan ensures high availability and fault tolerance by distributing data across elastically scalable clusters, making it suitable for use as either a volatile cache or a persistent data solution. By positioning data closer to the application logic, Infinispan enhances application performance through reduced latency and improved throughput. As a Java library, integrating Infinispan into your project is straightforward; all you need to do is include it in your application's dependencies, allowing you to efficiently manage data within the same memory environment as your executing code. Furthermore, its flexibility makes it an ideal choice for developers seeking to optimize data access in high-demand scenarios.

VMware Tanzu GemFire is a high-speed, distributed in-memory key-value storage solution that excels in executing read and write operations. It provides robust parallel message queues, ensuring continuous availability and an event-driven architecture that can be dynamically scaled without any downtime. As the demand for data storage grows to accommodate high-performance, real-time applications, Tanzu GemFire offers effortless linear scalability. Unlike traditional databases, which may lack the necessary reliability for microservices, Tanzu GemFire serves as an essential caching solution in modern distributed architectures. This platform enables applications to achieve low-latency responses for data retrieval while consistently delivering up-to-date information. Furthermore, applications can subscribe to real-time events, allowing them to quickly respond to changes as they occur. Continuous queries in Tanzu GemFire alert your application when new data becomes accessible, significantly reducing the load on your SQL database and enhancing overall performance. By integrating Tanzu GemFire, organizations can achieve a seamless data management experience that supports their growing needs.

Upscaledb is a high-speed key-value database that enhances storage efficiency and algorithms based on the unique characteristics of your data. It features optional compression that minimizes both file size and input/output operations, allowing for more data to reside in memory, which boosts performance and scalability during extensive table scans for querying and analyzing information. Upscaledb is capable of supporting all functionalities typical of a conventional SQL database, customized to align with the specific requirements of your application, and can be seamlessly integrated into your software. With its incredibly swift analytical capabilities and efficient database cursors, it serves as an ideal solution for processing data in scenarios where traditional SQL databases may falter in speed. This versatile database has found its applications across tens of millions of desktops, as well as on cloud servers, mobile devices, and various embedded systems. In a specific benchmark, a comprehensive table scan was conducted over 50 million records, yielding the highest retrieval speed, with the records set up as uint32 values, showcasing its remarkable efficiency. Furthermore, this performance highlights the potential of upscaledb to handle large datasets with ease, making it a preferred choice for developers seeking optimal data management solutions.

PolarDB-X has proven its reliability during the Tmall Double 11 shopping events and has assisted clients in various sectors, including finance, logistics, energy, e-commerce, and public services, in overcoming their business obstacles. It offers scalable storage solutions that can expand linearly to accommodate petabyte-scale demands, thereby eliminating the constraints associated with traditional standalone databases. Additionally, it features massively parallel processing (MPP) capabilities that greatly enhance the efficiency of performing complex analyses and executing queries on large datasets. Furthermore, it employs sophisticated algorithms to distribute data across multiple storage nodes, which effectively minimizes the amount of data held within individual tables. This advanced architecture not only optimizes performance but also ensures that businesses can handle their data needs flexibly and efficiently.

CockroachDB: Cloud-native distributed SQL. Your cloud applications deserve a cloud-native database. Cloud-based apps and services need a database that can scale across clouds, reduces operational complexity, and improves reliability. CockroachDB provides resilient, distributed SQL with ACID transactions. Data partitioned by geography is also available. Combining CockroachDB and orchestration tools such as Mesosphere DC/OS and Kubernetes to automate mission-critical applications can speed up operations.

Apache Trafodion serves as a webscale SQL-on-Hadoop solution that facilitates transactional or operational processes within the Apache Hadoop ecosystem. By leveraging the inherent scalability, elasticity, and flexibility of Hadoop, Trafodion enhances its capabilities to ensure transactional integrity, which opens the door for a new wave of big data applications to operate seamlessly on Hadoop. The platform supports the full ANSI SQL language, allowing for JDBC/ODBC connectivity suitable for both Linux and Windows clients. It provides distributed ACID transaction protection that spans multiple statements, tables, and rows, all while delivering performance enhancements specifically designed for OLTP workloads through both compile-time and run-time optimizations. Trafodion is also equipped with a parallel-aware query optimizer that efficiently handles large datasets, enabling developers to utilize their existing SQL knowledge and boost productivity. Furthermore, its distributed ACID transactions maintain data consistency across various rows and tables, making it interoperable with a wide range of existing tools and applications. This solution is neutral to both Hadoop and Linux distributions, providing a straightforward integration path into any existing Hadoop infrastructure. Thus, Apache Trafodion not only enhances the power of Hadoop but also simplifies the development process for users.

A Kudu cluster comprises tables that resemble those found in traditional relational (SQL) databases. These tables can range from a straightforward binary key and value structure to intricate designs featuring hundreds of strongly-typed attributes. Similar to SQL tables, each Kudu table is defined by a primary key, which consists of one or more columns; this could be a single unique user identifier or a composite key such as a (host, metric, timestamp) combination tailored for time-series data from machines. The primary key allows for quick reading, updating, or deletion of rows. The straightforward data model of Kudu facilitates the migration of legacy applications as well as the development of new ones, eliminating concerns about encoding data into binary formats or navigating through cumbersome JSON databases. Additionally, tables in Kudu are self-describing, enabling the use of standard analysis tools like SQL engines or Spark. With user-friendly APIs, Kudu ensures that developers can easily integrate and manipulate their data. This approach not only streamlines data management but also enhances overall efficiency in data processing tasks.

Smart DIH is a data management platform that quickly serves applications with accurate, fresh and complete data, delivering high performance, ultra-low latency, and an always-on digital experience. Smart DIH decouples APIs from SoRs, replicating critical data, and making it available using event-driven architecture. Smart DIH enables drastically shorter development cycles of new digital services, and rapidly scales to serve millions of concurrent users – no matter which IT infrastructure or cloud topologies it relies on. XAP Skyline is a distributed in-memory development platform that delivers transactional consistency, combined with extreme event-based processing and microsecond latency. The platform fuels core business solutions that rely on instantaneous data, including online trading, real-time risk management and data processing for AI and large language models.

Bolt is a key/value store written entirely in Go, drawing inspiration from Howard Chu's LMDB project. The primary aim of this initiative is to offer a straightforward, quick, and dependable database solution for smaller projects that do not need the complexity of a full-fledged database server like Postgres or MySQL. Given that Bolt serves as a foundational component, a focus on simplicity is paramount. The API is intentionally minimal, emphasizing only the essential operations of retrieving and storing values. This streamlined approach was central to Bolt's original vision: to create an uncomplicated pure Go key/value store without overwhelming it with unnecessary features. Consequently, the project has successfully achieved this goal. Nonetheless, the narrowly defined scope has led to the conclusion of the project's development. Managing an open source database is a labor-intensive endeavor that demands significant time and resources. Any modifications to the codebase can have unforeseen and potentially severe consequences, making even minor adjustments necessitate extensive testing and validation over prolonged periods. Additionally, the project's limited functionality allows users to focus on core database operations without the distractions of a more complex system.

What makes eXtremeDB platform independent? - Hybrid storage of data. Unlike other IMDS databases, eXtremeDB databases are all-in-memory or all-persistent. They can also have a mix between persistent tables and in-memory table. eXtremeDB's Active Replication Fabric™, which is unique to eXtremeDB, offers bidirectional replication and multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more. - Row and columnar flexibility for time series data. eXtremeDB supports database designs which combine column-based and row-based layouts in order to maximize the CPU cache speed. - Client/Server and embedded. eXtremeDB provides data management that is fast and flexible wherever you need it. It can be deployed as an embedded system and/or as a clients/server database system. eXtremeDB was designed for use in resource-constrained, mission-critical embedded systems. Found in over 30,000,000 deployments, from routers to satellites and trains to stock market world-wide.

Couchbase distinguishes itself from other NoSQL databases by delivering an enterprise-grade, multicloud to edge solution that is equipped with the powerful features essential for mission-critical applications on a platform that is both highly scalable and reliable. This distributed cloud-native database operates seamlessly in contemporary dynamic settings, accommodating any cloud environment, whether it be customer-managed or a fully managed service. Leveraging open standards, Couchbase merges the advantages of NoSQL with the familiar structure of SQL, thereby facilitating a smoother transition from traditional mainframe and relational databases. Couchbase Server serves as a versatile, distributed database that integrates the benefits of relational database capabilities, including SQL and ACID transactions, with the adaptability of JSON, all built on a foundation that is remarkably fast and scalable. Its applications span various industries, catering to needs such as user profiles, dynamic product catalogs, generative AI applications, vector search, high-speed caching, and much more, making it an invaluable asset for organizations seeking efficiency and innovation.

InterSystems Cache®, a high-performance database, powers transaction processing applications all over the globe. It's used for everything, from mapping a million stars in the Milky Way to processing a trillion equity trades per day to managing smart energy grids. InterSystems has developed Cache, a multi-model (object-relational, key-value), DBMS and application server. InterSystems Cache offers multiple APIs that allow you to work with the same data simultaneously: key/value, relational/object, document, multidimensional, object, object, and object. Data can be managed using SQL, Java, node.js.NET, C++ and Python. Cache also offers an application server that hosts web apps (CSP, REST, SOAP and other types TCP access for Cache data).

Lucid is in the process of development, aiming to create a swift, secure, and decentralized key-value storage solution that users can access via an HTTP API. Additionally, we plan to incorporate features such as data persistence, encryption, WebSocket streaming, and replication, along with various other functionalities. Among these features are the storage of private keys, Internet of Things (IoT) capabilities for the collection and storage of statistical data, distributed caching, service discovery, distributed configuration management, and blob storage. Our goal is to deliver a comprehensive solution that meets diverse user needs while ensuring robust performance and security.

Valkey is a high-performance key/value datastore that is open source and designed to handle diverse workloads, including caching and message queuing, while also functioning as a primary database. With backing from the Linux Foundation, its open source status is guaranteed indefinitely. Valkey can be deployed as a standalone service or within a clustered environment, featuring options for replication and ensuring high availability. It provides a wide array of data types, such as strings, numbers, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, among others. Users have the ability to manipulate data structures directly with a comprehensive suite of commands. Additionally, Valkey offers native extensibility through built-in Lua scripting support and allows the use of module plugins to introduce new commands and data types. The latest version, Valkey 8.1, brings numerous enhancements that improve performance by reducing latency, boosting throughput, and optimizing memory consumption. This makes Valkey an increasingly efficient choice for developers looking for a flexible and powerful data management solution.

Develop high-speed, data-centric applications that can dynamically adapt to performance needs regardless of scale. Leverage the distinctive technology of Apache Geode, which integrates sophisticated methods for data replication, partitioning, and distributed processing. With a database-like consistency model, Apache Geode guarantees dependable transaction handling and employs a shared-nothing architecture that supports remarkably low latency, even under high concurrency. The platform allows for seamless data partitioning (sharding) and replication across nodes, enabling performance to grow in accordance with demand. Reliability is bolstered by maintaining redundant in-memory copies along with disk-based persistence. Additionally, it features rapid write-ahead logging (WAL) persistence, optimized for quick parallel recovery of individual nodes or the entire cluster, ensuring robust performance even during failures. This combination of features not only enhances efficiency but also significantly improves overall system resilience.

An adaptable and efficient key-value storage engine, both persistent and in-memory, is engineered for superior performance and resource optimization. It is crafted to effectively handle data on-disk and in-memory by identifying recurring patterns in serialized bytes, without limiting itself to any particular data model, be it SQL or NoSQL, or storage medium, whether it be Disk or RAM. The core system offers a variety of configurations that can be fine-tuned for specific use cases, while also aiming to incorporate automatic runtime adjustments by gathering and analyzing machine statistics and read-write behaviors. Users can manage data easily by utilizing well-known structures such as Map, Set, Queue, SetMap, and MultiMap, all of which can seamlessly convert to native collections in Java and Scala. Furthermore, it allows for conditional updates and data modifications using any Java, Scala, or native JVM code, eliminating the need for a query language and ensuring flexibility in data handling. This design not only promotes efficiency but also encourages the adoption of custom solutions tailored to unique application needs.

Greetings! BergDB is an efficient database built on Java and .NET, crafted for developers who want to concentrate on their tasks without getting bogged down by database complexities. It features straightforward key-value storage, ACID-compliant transactions, the ability to perform historic queries, effective concurrency management, secondary indices, swift append-only storage, replication capabilities, and seamless object serialization among other attributes. As an embedded, open-source, document-oriented, schemaless NoSQL database, BergDB is purposefully designed to deliver rapid transaction processing. Importantly, it ensures that all database writes adhere to ACID transactions, maintaining the highest consistency level available, which is akin to the serializable isolation level in SQL. The functionality of historic queries is beneficial for retrieving previous data states and managing concurrency efficiently, as read operations in BergDB are executed without locking any resources, allowing for smooth and uninterrupted access to data. This unique approach ensures that developers can work more productively, leveraging BergDB’s robust features to enhance application performance.

As the volume of traffic and user demands on your application grows, enhance its performance in a straightforward and economical way. Implementing a caching layer within your application architecture can efficiently manage thousands of concurrent users, providing near-instantaneous response times, all while leveraging the advantages of a fully managed service. Achieve remarkable throughput and performance capable of processing millions of requests per second with sub-millisecond latency. This fully managed service includes automatic updates, patching, scaling, and provisioning, allowing you to concentrate on development without distraction. Integration of modules like RedisBloom, RediSearch, and RedisTimeSeries empowers your application with comprehensive capabilities for data analysis, search functionality, and real-time streaming. You will benefit from robust features such as clustering, built-in replication, Redis on Flash, and an impressive availability rate of up to 99.99 percent, ensuring reliability. Furthermore, by complementing services like Azure SQL Database and Azure Cosmos DB, you can enhance your data tier's throughput scalability at a more economical rate compared to merely expanding database instances. Ultimately, these enhancements not only improve the user experience but also position your application for future growth and adaptability.

KeyDB ensures complete compatibility with Redis modules, APIs, and protocols, allowing for a seamless integration that retains the functionality of your existing clients, scripts, and configurations. You can effortlessly switch to KeyDB while maintaining this compatibility. Its Multi-Master mode provides a single replicated dataset across multiple nodes, facilitating both read and write operations. Additionally, nodes can be replicated across different regions to achieve submillisecond latencies for local clients. With Cluster mode, the dataset can be divided across shards, enabling limitless read and write scalability while simultaneously supporting high availability through replica nodes. KeyDB also introduces new community-driven commands that enhance your ability to manipulate data. You can create your own commands and features using JavaScript via the ModJS module, which allows for the writing of functions in JavaScript that can be directly invoked by KeyDB. An example of a JavaScript function that could be loaded with this module is provided on the left, demonstrating how it can be called directly from your client, showcasing the flexibility and power of KeyDB. This capability not only enhances your data handling but also fosters a more dynamic interaction with your database environment.

Effortlessly handle intricate models with ArcadeDB while ensuring no compromises are made. Say goodbye to the concept of Polyglot Persistence; there's no need to juggle multiple databases. With ArcadeDB's Multi-Model database, you can seamlessly store graphs, documents, key values, and time series data in one unified solution. As each model is inherently compatible with the database engine, you can avoid the delays caused by translation processes. Powered by advanced Alien Technology, ArcadeDB's engine can process millions of records every second. Notably, the speed of data traversal remains constant regardless of the database's size, whether it houses a handful of records or billions. ArcadeDB is versatile enough to function as an embedded database on a single server and can easily scale across multiple servers using Kubernetes. Its compact design allows it to operate on any platform while maintaining a minimal footprint. Your data's security is paramount; our robust, fully transactional engine guarantees durability for mission-critical production databases. Additionally, ArcadeDB employs a Raft Consensus Algorithm to ensure consistency and reliability across multiple servers, making it a top choice for data management. In an era where efficiency and reliability are crucial, ArcadeDB stands out as a comprehensive solution for diverse data storage needs.

Volt Active Data is a sophisticated data platform designed to streamline your entire technology stack, enhancing speed and cost-effectiveness, enabling applications and businesses to effortlessly scale in alignment with the extremely low latency service level agreements (SLAs) demanded by 5G, IoT, edge computing, and future innovations. It is tailored to complement your current big data assets, including NoSQL, Hadoop, Kubernetes, Kafka, and conventional databases or data warehouses, as it replaces the multiple layers usually necessary for making contextual decisions on streaming data with a singular, cohesive layer that facilitates ingestion to action in under 10 milliseconds. The digital landscape is inundated with data that is generated, stored, often overlooked, and ultimately discarded. "Active Data" refers to the information that requires immediate action for businesses to derive value from it. Numerous traditional and NoSQL data storage solutions are available for managing such data; however, there exists also a category of data that can be monetized, provided that swift action is taken to 'influence the moment' before the opportunity slips away. By harnessing the capabilities of Volt Active Data, organizations can ensure they are not merely collecting data but effectively leveraging it for real-time decision-making and strategic advantage.

BigchainDB functions as a database infused with blockchain features, offering high throughput, low latency, advanced query capabilities, decentralized governance, permanent data storage, and integrated asset management. This platform enables both developers and businesses to create blockchain proof-of-concepts, applications, and platforms, catering to a diverse array of industries and practical applications. Instead of enhancing existing blockchain technology, BigchainDB uniquely merges a large-scale distributed database with blockchain traits—such as decentralized governance, data immutability, and digital asset transfer. Its architecture eliminates any single point of control or failure, utilizing a federation of voting nodes to establish a peer-to-peer network. Users can execute any MongoDB query to sift through the entirety of stored transactions, assets, metadata, and blocks, leveraging the robust capabilities of MongoDB as its backbone. This innovative approach not only streamlines data management but also enriches the user experience by ensuring reliability and efficiency in digital asset transactions.