Best Data Management Software for Tonic Ephemeral

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

Amazon DynamoDB, a key-value and document databank, delivers single-digit millisecond performance on any scale. It is a fully managed, multiregional, multimaster, durable database that offers built-in security, backup, restore, and in-memory cache for internet-scale apps. DynamoDB can process more than 10 trillion requests per hour and can handle peak requests of more than 20,000,000 requests per second. Many of the fastest-growing businesses in the world, such as Lyft, Redfin, and Airbnb, as well as enterprises like Samsung, Toyota and Capital One, rely on DynamoDB's scale and performance to support mission-critical workloads.

MySQL is the most widely used open-source database in the world. MySQL is the most popular open source database for web-based applications. It has been proven to be reliable, performant, and easy-to-use. This database is used by many high-profile web properties, including Facebook, Twitter and YouTube. It is also a popular choice for embedded databases, distributed by thousands ISVs and OEMs.

Your cloud data platform. Access to any data you need with unlimited scalability. All your data is available to you, with the near-infinite performance and concurrency required by your organization. You can seamlessly share and consume shared data across your organization to collaborate and solve your most difficult business problems. You can increase productivity and reduce time to value by collaborating with data professionals to quickly deliver integrated data solutions from any location in your organization. Our technology partners and system integrators can help you deploy Snowflake to your success, no matter if you are moving data into Snowflake.

Microsoft SQL Server 2019 includes intelligence and security. You get more without paying extra, as well as best-in-class performance for your on-premises requirements. You can easily migrate to the cloud without having to change any code. Azure makes it easier to gain insights and make better predictions. You can use the technology you choose, including open-source, and Microsoft's innovations to help you develop. Integrate data into your apps easily and access a rich set cognitive services to build human-like intelligence on any data scale. AI is built into the data platform, so you can get insights faster from all of your data, both on-premises or in the cloud. To build an intelligence-driven company, combine your enterprise data with the world's data. You can build your apps anywhere with a flexible platform that offers a consistent experience across platforms.

Amazon Redshift is preferred by more customers than any other cloud data storage. Redshift powers analytic workloads for Fortune 500 companies and startups, as well as everything in between. Redshift has helped Lyft grow from a startup to multi-billion-dollar enterprises. It's easier than any other data warehouse to gain new insights from all of your data. Redshift allows you to query petabytes (or more) of structured and semi-structured information across your operational database, data warehouse, and data lake using standard SQL. Redshift allows you to save your queries to your S3 database using open formats such as Apache Parquet. This allows you to further analyze other analytics services like Amazon EMR and Amazon Athena. Redshift is the fastest cloud data warehouse in the world and it gets faster each year. The new RA3 instances can be used for performance-intensive workloads to achieve up to 3x the performance compared to any cloud data warehouse.

IBM Db2®, a family of hybrid data management tools, offers a complete suite AI-empowered capabilities to help you manage structured and unstructured data both on premises and in private and public clouds. Db2 is built upon an intelligent common SQL engine that allows for flexibility and scalability.

AWS Glue, a fully managed extract-transform-and-load (ETL) service, makes it easy for customers prepare and load their data for analysis. With just a few clicks, you can create and run ETL jobs. AWS Glue simply points to the AWS Data Catalog and AWS Glue finds your data and stores metadata (e.g. AWS Glue Data Catalog contains the table definition and schema. Once your data has been cataloged, it is immediately searchable and queryable. It is also available for ETL.

MariaDB Platform is an enterprise-level open-source database solution. It supports transactional, analytical, and hybrid workloads, as well as relational and JSON data models. It can scale from standalone databases to data warehouses to fully distributed SQL, which can execute millions of transactions per second and perform interactive, ad-hoc analytics on billions upon billions of rows. MariaDB can be deployed on prem-on commodity hardware. It is also available on all major public cloud providers and MariaDB SkySQL, a fully managed cloud database. MariaDB.com provides more information.

Oracle database products offer customers cost-optimized, high-performance versions Oracle Database, the world's most popular converged, multi-model database management software. They also include in-memory NoSQL and MySQL databases. Oracle Autonomous Database is available on-premises via Oracle Cloud@Customer and in the Oracle Cloud Infrastructure. It allows customers to simplify relational databases environments and reduce management burdens. Oracle Autonomous Database reduces the complexity of operating and protecting Oracle Database, while delivering the highest levels performance, scalability and availability to customers. Oracle Database can also be deployed on-premises if customers have network latency and data residency concerns. Customers who depend on Oracle database versions for their applications have full control over which versions they use and when they change.

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.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.

Amazon EMR is the market-leading cloud big data platform. It processes large amounts of data with open source tools like Apache Spark, Apache Hive and Apache HBase. EMR allows you to run petabyte-scale analysis at a fraction of the cost of traditional on premises solutions. It is also 3x faster than standard Apache Spark. You can spin up and down clusters for short-running jobs and only pay per second for the instances. You can also create highly available clusters that scale automatically to meet the demand for long-running workloads. You can also run EMR clusters from AWS Outposts if you have on-premises open source tools like Apache Spark or Apache Hive.

Parquet was created to provide the Hadoop ecosystem with the benefits of columnar, compressed data representation. Parquet was built with complex nested data structures and uses the Dremel paper's record shredding/assemblage algorithm. This approach is better than flattening nested namespaces. Parquet is designed to support efficient compression and encoding strategies. Multiple projects have shown the positive impact of the right compression and encoding scheme on data performance. Parquet allows for compression schemes to be specified per-column. It is future-proofed to allow for more encodings to be added as they are developed and implemented. Parquet was designed to be used by everyone. We don't want to play favorites in the Hadoop ecosystem.

Azure Databricks allows you to unlock insights from all your data, build artificial intelligence (AI), solutions, and autoscale your Apache Spark™. You can also collaborate on shared projects with other people in an interactive workspace. Azure Databricks supports Python and Scala, R and Java, as well data science frameworks such as TensorFlow, PyTorch and scikit-learn. Azure Databricks offers the latest version of Apache Spark and allows seamless integration with open-source libraries. You can quickly spin up clusters and build in an Apache Spark environment that is fully managed and available worldwide. Clusters can be set up, configured, fine-tuned, and monitored to ensure performance and reliability. To reduce total cost of ownership (TCO), take advantage of autoscaling or auto-termination.

Amazon DocumentDB (with MongoDB compatibility), is a fast, scalable and highly available document database service that supports MongoDB workloads. Amazon DocumentDB is a document database that makes it easy to store, query and index JSON data. Amazon DocumentDB is a nonrelational database service that was designed from the ground up to provide the performance, scalability and availability you require when running mission-critical MongoDB workloads on a large scale. Amazon DocumentDB is decoupled from compute and storage, which allows each to scale independently. You can increase read capacity to millions of requests every second by adding up 15 low latency replicas in minutes, regardless how large your data is. Amazon DocumentDB is designed to guarantee 99.99% availability. It replicates six copies across three AWSAvailability Zones (AZs) of your data.