Alternatives to TimescaleDB

Cloud SQL is a fully managed relational database service that supports MySQL, PostgreSQL and SQL Server. It includes rich extensions, configuration flags and developer ecosystems. Cloud SQL offers $300 in credits for new customers. You won't pay until you upgrade. Reduce maintenance costs by using fully managed MySQL PostgreSQL SQL Server databases. SRE team provides 24/7 support for reliable and secure services. Data encryption in transit and at rest. Private connectivity with Virtual Private Cloud, user-controlled network access and firewall protection. Compliant with SSAE 16 ISO 27001 PCI DSS and HIPAA. Scale your database instances with a single API request, whether you are just testing or need a highly-available database in production. Standard connection drivers and integrated migration tools let you create and connect to a database in a matter of minutes.

Raima Database Manager, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.

Amazon Timestream is a fast, scalable and serverless time series data service for IoT/operational applications. It makes it possible to store and analyze trillions per day up to 1000 times faster than traditional relational databases and at as low as 1/10th of the cost. Amazon Timestream helps you save time and money when managing the lifecycles of time series data. It stores recent data in memory and moves historical data to a cost-optimized storage tier according to user defined policies. Amazon Timestream's purpose-built query tool allows you to access and analyze both recent and historic data simultaneously, without having to specify in the query whether the data is in the in-memory tier or the cost-optimized. Amazon Timestream's built-in time series analytics functions allow you to identify trends and patterns within your data in real-time.

ScaleGrid is a fully managed Database-as-a-Service (DBaaS) platform that helps you automate your time-consuming database administration tasks both in the cloud and on-premises. ScaleGrid makes it easy to provision, monitor, backup, and scale open-source databases. It offers advanced security, high availability, query analysis, and troubleshooting support to improve your deployments' performance. The following databases are supported: - MySQL - PostgreSQL - Redis™. - MongoDB®, database - Greenplum™ (coming soon) ScaleGrid supports both public and privately-owned clouds such as AWS, Azure and Google Cloud Platform (GCP), DigitalOcean and Linode, Oracle Cloud Infrastructure, (OCI), VMware, and OpenStack. ScaleGrid is used by thousands of developers, startups, as well as enterprise customers such as Accenture, Meteor and Atlassian. It handles all your database operations at any scale, so you can concentrate on your application performance.

GridDB uses multicast communication in order to create a cluster. To enable multicast communication, set the network. First, verify the host name and IP address. To check the settings for an IP address on the host, run "hostname-i" command. If the IP address of your machine is identical to the below, you don't need to adjust network settings and can skip to the next section. GridDB is a database that manages a group (known as a Row) of data that is composed of multiple values and a key. It can be an in-memory database which arranges all data in the memory. However, it can also use a hybrid composition that uses both a disk (including SSD) and a memory.

InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge. To get started, InfluxData offers free training through InfluxDB University.

SiriDB is optimized for speed. Inserts and queries are answered quickly. You can speed up your development with the custom query language. SiriDB is flexible and can be scaled on the fly. There is no downtime when you update or expand your database. You can scale your database without losing speed. As we distribute your time series data across all pools, we make full use of all resources. SiriDB was designed to deliver unmatched performance with minimal downtime. A SiriDB cluster distributes time series across multiple pools. Each pool has active replicas that can be used for load balancing or redundancy. The database can still be accessed even if one of the replicas is unavailable.

OpenTSDB is composed of a Time Series Daemon, (TSD), and a set of command-line utilities. OpenTSDB can only be interacted with by one or more TSDs. Each TSD can be run independently. There is no master or shared state, so you can run as many TSDs you need to handle any load. Each TSD uses the HBase open-source database or hosted Google Bigtable service for time-series data storage and retrieval. The data schema is optimized for fast aggregations and retrieval of similar time series, minimizing storage space. The TSD does not require users to directly access the underlying store. The TSD can be communicated with via a simple telnet protocol, an HTTP API, or a built-in GUI. OpenTSDB's first step is to send time series data directly to the TSDs. OpenTSDB has many tools that allow you to pull data from different sources.

QuestDB is a relational database that uses column-oriented databases. It can be used for event and time series data. It uses SQL with extensions to time series to aid in real-time analytics. These pages provide information about core concepts of QuestDB. They include setup steps, usage guides, as well as reference documentation for syntax, APIs, and configuration. This section explains the architecture of QuestDB and how it stores and queries data. It also introduces new capabilities and features that are unique to the system. The core feature of QuestDB is the designated timestamp. It enables partitioning and time-oriented language capabilities. The symbol type makes it easy to store and retrieve repetitive strings. QuestDB's storage model describes how it stores records and partitions within tables. Indexes can be used to provide faster access to specific columns. Partitions can be used to provide significant performance improvements in calculations and queries. SQL extensions enable time series analysis that is efficient and concise with a concise syntax.

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

Apache Druid, an open-source distributed data store, is Apache Druid. Druid's core design blends ideas from data warehouses and timeseries databases to create a high-performance real-time analytics database that can be used for a wide range of purposes. Druid combines key characteristics from each of these systems into its ingestion, storage format, querying, and core architecture. Druid compresses and stores each column separately, so it only needs to read the ones that are needed for a specific query. This allows for fast scans, ranking, groupBys, and groupBys. Druid creates indexes that are inverted for string values to allow for fast search and filter. Connectors out-of-the box for Apache Kafka and HDFS, AWS S3, stream processors, and many more. Druid intelligently divides data based upon time. Time-based queries are much faster than traditional databases. Druid automatically balances servers as you add or remove servers. Fault-tolerant architecture allows for server failures to be avoided.

Proficy Historian, a top-of-the-line historian software solution, collects industrial time-series data and A&E data at a high speed, stores it securely and efficiently, distributes it, and allows fast retrieval and analysis. This results in greater business value. Proficy Historian has thousands of satisfied customers around the globe and decades of experience. It makes data available for process and asset performance analysis. Proficy Historian's latest version improves usability, configuration and maintainability by making significant architectural improvements. The solution's powerful yet simple features will allow you to unlock new value for your equipment, process data and business models. Remote collector management with UX. Horizontal scaling that allows enterprise-wide data visibility

IBM Informix®, a fast and flexible database that can seamlessly integrate SQL, NoSQL/JSON and time series data, is available. Informix's versatility and ease-of-use make it a popular choice for a wide variety of environments, including enterprise data warehouses and individual application development. Informix is also well-suited for embedded data management solutions due to its small footprint and self-managing capabilities.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

High performance, fully managed and hosted PostgreSQL. All the extensions you need right out of the box. You can set up fully managed PostgreSQL within 10 minutes using our web console, or programmatically via our API or CLI, Terraform provider, or Kubernetes operators. Stand-by nodes can be used as read replicas. You can also create additional read replicas in other public clouds or regions. Our Point-In-Time-Recovery lets you restore your data to any time within your selected retention period. Fully managed SQL relational database that can be deployed in the cloud of choice. It is known for its reliability, robust features, and exceptional performance. It can be used in almost any situation, including creating location-based services, mission-critical business applications, or as a general transactional data base.

Machbase is a time-series database that stores, analyzes, and displays a lot sensor data from different facilities in real time. It is the only DBMS that can process big data at high speed. Machbase's incredible speed is amazing! It is the most innovative product to enable real-time processing, storage and analysis of sensor data. DBMS embedded in Edge devices allows for high speed storage and inquiry of sensor data. DBMS running on a single server provides the best data storage and extraction performance. Multi-node cluster configuration with the benefits of availability and scaleability. Edge computing is a complete management solution for device, connectivity, and data.

QuasarDB is Quasar's brain. It is a high-performance distributed, column-oriented, timeseries database management software system that delivers real-time data for petascale use cases. You can save up to 20X on your disk usage Quasardb compression and ingestion are unmatched. Feature extraction can be performed up to 10,000 times faster. QuasarDB is able to extract features from raw data in real-time thanks to a combination of a builtin map/reduce engine, an aggregate engine that leverages SIMD from modern processors, and stochastic indices that consume virtually no disk space.

Riak®, TS is an enterprise-grade NoSQL Time Series Database that is specifically designed for IoT data and Time Series data. It can ingest, transform, store, and analyze massive amounts of time series information. Riak TS is designed to be faster than Cassandra. Riak TS masterless architecture can read and write data regardless of network partitions or hardware failures. Data is evenly distributed throughout the Riak ring. By default, there are three copies of your data. This ensures that at least one copy is available for reading operations. Riak TS is a distributed software system that does not have a central coordinator. It is simple to set up and use. It is easy to add or remove nodes from a cluster thanks to the masterless architecture. Riak TS's masterless architecture makes it easy for you to add or remove nodes from your cluster. Adding nodes made of commodity hardware to your cluster can help you achieve predictable and almost linear scale.

Fujitsu Enterprise Postgres, a highly reliable and robust relational database designed for organizations that need high query performance and high availability, is a great choice. It is built on the well-respected open-source PostgreSQL system, and includes enterprise-grade features that enhance security and performance. Fujitsu Enterprise Postgres is managed and installed by Fujitsu's database specialists. They can also help with data migration from your existing database. FEP, which is based on PostgreSQL has high compatibility with other systems and applications. The graphic user interface is simple and clean, which makes it easier for DBAs to execute core database functions such as scanning, queries, and back-up. This makes your data and reports more accessible.

High-performance, cross-platform columnar historical time-series columnar data featuring: - An in-memory computation engine - A streaming processor that streams real-time - A combination of a programming language and expressive query, q

VictoriaMetrics is a cost-effective, scalable monitoring solution that can also be used as a time series database. It can also be used to store Prometheus' long-term data. VictoriaMetrics is a single executable that does not have any external dependencies. All configuration is done using explicit command-line flags and reasonable defaults. It provides global query view. Multiple Prometheus instances, or other data sources, may insert data into VictoriaMetrics. Later this data may be queried via a single query. It can handle high cardinality and high churn rates issues by using a series limiter.

Use CA's Web-enabled, high performance mainframe relational database management software to achieve superior database performance at a low cost and maximum flexibility.

Postico is a database client. Postico can connect to either a local PostgreSQL Server on your Mac or remote servers on a different computer. Postgres.app is a great option if you are looking to install a local PostgreSQL Server on your Mac. Postgres.app will create a PostgreSQL Server on your Mac. It will create a new directory and an empty database the first time it starts. After a few seconds, the server will start and wait for connections. Postgres.app cannot start if another PostgreSQL Server is running on your computer. If you have problems, make sure to deactivate and uninstall any other PostgreSQL servers. Reboot your computer after uninstalling! First, create a favorite to connect to a PostgreSQL Server with Postico. A favorite contains parameters that allow you to connect to a server. Some parameters for connecting to a server are optional.

HEAVY.AI is a pioneer in accelerated analysis. The HEAVY.AI platform can be used by government and business to uncover insights in data that is beyond the reach of traditional analytics tools. The platform harnesses the huge parallelism of modern CPU/GPU hardware and is available both in the cloud or on-premise. HEAVY.AI was developed from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory. You can go beyond traditional BI and GIS and extract high-quality information from large datasets with no lag by leveraging modern GPU and CPU hardware. To get a complete picture of what, when and where, unify and explore large geospatial or time-series data sets. Combining interactive visual analytics, hardware accelerated SQL, advanced analytics & data sciences frameworks, you can find the opportunity and risk in your enterprise when it matters most.

Time Series Database (TSDB), supports high-speed data writing and reading. It has high compression ratios to ensure data storage costs are low. This service supports visualization of precision reduction and interpolation, multimetric aggregate computing, as well as query results. The TSDB service lowers storage costs and improves data writing, query, analysis efficiency. This allows you to manage large numbers of data points and collect more data. This service is widely used in a variety of industries, including IoT monitoring systems and enterprise energy management systems (EMSs), power supply monitoring systems, production security monitoring systems, and IoT monitoring. Optimizes database architectures. TSDB can read and write millions of data points in seconds. Uses an efficient compression algorithm that reduces the data point's size to 2 bytes. This saves more than 90% on storage costs.

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is five times faster that standard MySQL databases and three time faster than standard PostgreSQL database. It offers the same security, availability, reliability, and cost-effectiveness as commercial databases, but at a fraction of the cost. Amazon Aurora is fully managed and maintained by Amazon Relational Database Service, (RDS). This automates tedious administration tasks such as hardware provisioning, database setup, patching and backups. Amazon Aurora is a distributed, fault-tolerant and self-healing storage that auto-scales up 64TB per database instance. It offers high availability and performance with up to 15 low latency read replicas, point in time recovery, continuous backup to Amazon S3, replication across threeAvailability Zones, and continuous backup to Amazon S3.

Blueflood, a distributed metric processing system that is high throughput and low latency for multi-tenant multi-tenants, is behind Rackspace Metrics. It is currently being used in production by Rackspace Monitoring team as well as Rackspace public cloud team to store metrics created by their systems. Blueflood is also used in large-scale Rackspace deployments. Blueflood data can be used to create dashboards, reports, graphs, or any other use that involves time-series information. It is focused on near-realtime data and data that can be queryable within milliseconds of ingestion. You send metrics to ingestion service. The Query service allows you to query your metrics. Rollups are processed offline in the background so that queries with long time periods are quickly returned.

The beauty of Canary Historian's solution is that it works on-site as well as for the entire enterprise. You can log data locally and send it to your enterprise historian simultaneously. The best part is that the solution grows with you. A single Canary Historian is capable of logging more than two million tags. Multiple Canary Historians can also be clustered to manage tens of thousands of tags. Enterprise historian solutions can be hosted in either your own data centers, or in AWS or Azure. Canary Historians are not dependent on specialized teams of ten or more to maintain, unlike other enterprise history solutions. The Canary Historian, a NoSQL time-series database, uses loss-less compression algorithms for high-speed performance without data interpolation.

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.

PostgreSQL, a powerful open-source object-relational database system, has over 30 years of experience in active development. It has earned a strong reputation for reliability and feature robustness.

LeanXcale is fast and scalable database that combines SQL and NoSQL. It can ingest large batches of data and make it available via SQL or GIS for any purpose, including operational applications, analytics and dashboarding. No matter which stack you use, LeanXcale offers both SQL and NoSQL interfaces. The KiVi storage engine can be used as a relational key/value data store. The data can be accessed via the standard SQL API or a direct ACID key/value interface. This key-value interface allows users data ingestion at extremely high rates and efficiently, while avoiding SQL processing overhead. High-scalable, efficient, and distributed storage engine distributed data along a cluster to improve performance and increase reliability.

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.

KS DB Merge Tools is an easy to use diff & merge tool for MySQL, MariaDB, Oracle Database, SQL Server, PostgreSQL, MS Access, SQLite and Cross-DBMS databases allowing to compare and sync both schema and data. Starting with a schema changes summary, results can be narrowed down to object lists of particular object type (table definitions, views, etc.), and then down to definition of particular object. Data changes can be retrieved as a high-level list of changes totals across all tables in the database, each total row count can be observed as a side-by-side list of rows for the given table, each changed row can be analyzed for changes in each column. Various diff results provide quick filters to show only new/changed/new+changed items (schema objects or table data rows), ability to select required changed items and generate scripts to apply these changes to the other side database. This script can be executed immediately or saved for future use.

RDS for MySQL is a relational cloud database with high performance and reliability. It offers a simple and convenient web-based interface, reliable data backups and recovery features, as well as a complete security management service. RDS for MySQL is a relational database service that provides high-performance, high-reliability. It supports three series: stand-alone basic, dual high availability, and Raft Financial. It implements monitoring, automatic failureover, data backup, recovery, instance management and other features. It also meets the higher demands of customers for data management and storage, through slow SQL statistics, diagnosis, and reliable services such as cross domain hot instance groups. It supports disaster recovery for a single availability area and disaster recovery across multiple availability zones.

OneTick Database is embraced by top banks, brokerages and data vendors as well as exchanges, markets, hedge funds, market makers, mutual funds and other financial institutions. OneTick is the best enterprise-wide solution for tick data collection, streaming analytics and data management. OneTick is loved by top hedge funds, mutual funds and banks as well as brokers, banks, brokerages and market makers. OneTick's proprietary time-series database is a unified platform for multi-asset classes. It includes a fully integrated streaming analytics engine, built-in business logic, and eliminates the need to use multiple disparate systems. The system has the lowest total cost-of-ownership.

Circonus IRONdb makes it simple to store and manage unlimited volumes of Telemetry data. It can also handle billions of metric streams. Circonus IRONdb allows users to identify areas where there is opportunity and challenges in real-time. It provides forensic, predictive and automated analytics capabilities that are unmatched by any other product. Machine learning can automatically establish a "new norm" for your data and operations as they change. Circonus IRONdb is compatible with Grafana which supports our analytics query language. We also work with Graphite-web and other visualization apps. Circonus IRONdb protects your data by storing multiple copies in a cluster IRONdb nodes. Clustering is often managed by system administrators, who spend considerable time maintaining it and keeping the system running. Circonus IRONdb allows operators the ability to set and forget their cluster and stop manually managing their time series data stores.

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.

ArcadeDB allows you to manage complex models without any compromises. Polyglot Persistence is gone. There is no need to have multiple databases. ArcadeDB Multi-Model databases can store graphs and documents, key values, time series, and key values. Each model is native to the database engine so you don't need to worry about translations slowing down your computer. ArcadeDB's engine was developed with Alien Technology. It can crunch millions upon millions of records per second. ArcadeDB's traversing speed does not depend on the size of the database. It doesn't matter if your database contains a few records or a billion. ArcadeDB can be used as an embedded database on a single server. It can scale up by using Kubernetes to connect multiple servers. It is flexible enough to run on any platform that has a small footprint. Your data is protected. Our unbreakable fully transactional engine ensures durability for mission-critical production database databases. ArcadeDB uses the Raft Consensus Algorithm in order to maintain consistency across multiple servers.

SAP HANA is an in-memory database with high performance that accelerates data-driven decision-making and actions. It supports all workloads and provides the most advanced analytics on multi-model data on premise and in cloud.

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.

If you are one of the many organizations migrating a commercial database to open source, such as MySQL and PostgreSQL or if your company is building new applications using open-source database management system (OSDBMS), you will know that there is no commercial tooling available for these databases. Imagine if you could save money and be able to quickly ramp up your business using a familiar tool set. Toad Edge® makes it possible. It's a lightweight and reliable desktop tool that simplifies the development and management of open-source databases. Toad for MySQL or PostgreSQL management makes learning new databases easy. Toad Edge is a great tool for MariaDB, Amazon Redshift, and EDB Postgres Advanced Server. Toad Edge supports coding and editing, schema compare, sync, and DevOps CI processes so that you can manage open-source databases quickly and confidently.

With relational database management systems (RDBMS), solutions from SAP SQL Anywhere, you can run your business from anywhere. Secure, reliable data management for servers without a DBA. Also, synchronization for thousands of mobile devices, IoT systems, and remote environments. Remote offices and mobile devices can receive critical business data for faster, more accurate decision-making. Mobile applications can be run reliably and efficiently even without the need for technical staff. This gives remote workers and mobile workers a seamless experience, even when they're not on-site. With built-in self-managing capabilities, users can streamline data maintenance tasks and resolve issues quickly and efficiently. Strong encryption features can help protect and secure your data even during data exchange and transmission.

Free to create, manage, query, and explore Valentina DB and SQLite databases. You can create business reports in Valentina Studio Pro, Valentina Server, or in an application using an Application Developer Kit. Standard backward engineering with forwarding engineering in Valentina Studio Pro Create diagrams from existing databases and reverse engineering. Add new objects to diagrams. SQL queries can be written with color syntax and auto-completion. Define, manage, save favorite queries; access recent queries. Each function has a function browser dictionary. Consoles for errors and warnings. Search, Export result records to CSV, JSON or Excel. Edit multiple properties at once. You can drill down to fields and tables; it is a fast way to search. Create diagrams from existing databases by reverse engineering. Diagrams can be updated with new objects. Manage privileges and users by adding and dropping users and groups.

JaguarDB allows for fast ingestion of time-series data and location-based data. It can also index in both time and space. It is also quick to back-fill time series data (inserting large amounts of data in the past time). Time series are usually a sequence of data points that have been indexed in order of time. JaguarDB uses the term time series to mean both a sequence data points and a set of tick tables that hold aggregated data values over a specified time span. JaguarDB's time series tables can contain a base table that stores data points in time order and tick tables such daily, weekly, monthly, and daily tables to store aggregated information within these time periods. The RETENTION format is identical to the TICK format, but it can have any number or retention periods. The RETENTION indicates how long data points in the base tables should be kept.

PipelineDB is a PostgreSQL extension that allows high-performance time series aggregation. It's designed to power real-time reporting and analytics. PipelineDB allows the creation of continuous SQL queries that continuously aggregate time-series data, and store only the aggregate output into regular, queryable tables. This concept can be described as highly-accurate, incrementally updated materialized views that do not need to be manually refreshed. PipelineDB is extremely efficient in aggregation workloads because raw time-series data are never written to disk. Continuous queries can be linked together to create arbitrary networks of continuous SQL by creating their own output streams.

Open-source monitoring solutions are able to power your alerting and metrics. Prometheus stores all data in time series. These are streams of timestamped value belonging to the same metric with the same labeled dimensions. Prometheus can also generate temporary derived times series as a result of queries. Prometheus offers a functional query language called PromQL, which allows the user to select and aggregate time series data real-time. The expression result can be displayed as a graph or tabular data in Prometheus’s expression browser. External systems can also consume the HTTP API. Prometheus can be configured using command-line flags or a configuration file. The command-line flags can be used to configure immutable system parameters such as storage locations and the amount of data to be kept on disk and in memory. . Download: https://sourceforge.net/projects/prometheus.mirror/

Azure Time Series Intelligences Gen2 is an open-source, scalable IoT analytics service that can be integrated into existing workflows and applications. It can be used to collect, store, query, query, and visualize data at Internet of Things scale (IoT),-data that is highly contextualized and optimized in time series. Azure Time Series Insights Gen2 can be used for operational analysis and data exploration. It allows you to spot anomalies and uncover hidden trends. It is flexible and open to all industrial IoT deployments.

This service provides the full feature set of Informix on premises deployments at a fraction of the cost and complexity. It also reduces risk and lowers your overall infrastructure management costs. The IBM®, Informix®, on Cloud offering offers an Informix database on IBM Cloud®. Customers can enjoy the rich features of an Informix on-premises deployment, while reducing the cost, complexity, and risk of managing their own infrastructure. Informix on Cloud is a high-performance engine that combines time series, spatial and NoSQL data with easy access via MQTT, REST, and MongoDB APIs. Informix on Cloud makes cloud deployments easier and faster. It integrates spatial, NoSQL, time series, and SQL data. Flexible hosting and software licensing options can help reduce the complexity and cost of infrastructure maintenance. With 24/7 support, you can choose the right size for your business.

KX Streaming Analytics allows you to ingest and store historical and time series data. This data can then be processed, stored, processed, and analyzed instantly to provide analytics, insights, or visualizations. The platform offers the complete lifecycle of data services to ensure that your applications and users can be productive quickly. This includes query processing, query processing, tiering and migration, archiving and data protection. Our advanced analytics and visualization tools are widely used in finance and industry. They allow you to create and execute queries, calculations, aggregations and machine learning on any streaming or historical data. Data can be used across multiple hardware environments and can come from high-volume sources such as clickstreams, radio frequency identification, GPS systems and social networking sites.

KairosDB can push data via multiple protocols: Telnet Rest, Graphite, and Rest. You can also use plugins and other mechanisms. KairosDB stores time series using Cassandra NoSQL datastore. The schema is composed of three column families. This API allows you to list existing metric names, value tags, store metric data, and query for metric points. KairosDB will automatically install the query page. This page allows you to query data stored in the data store. It is intended for development purposes only. Aggregators can perform operations on data points and down samples. You can use standard functions such as min, max, sum and count to calculate the mean, mean, count, mean, and other parameters. The command line allows you to import and export data from the KairosDB server. The server's performance can be monitored internally by the data store.