Best OLAP Databases for Docker

Find and compare the best OLAP Databases for Docker in 2024

Use the comparison tool below to compare the top OLAP Databases for Docker on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    SingleStore Reviews

    SingleStore

    SingleStore

    $0.69 per hour
    1 Rating
    SingleStore (formerly MemSQL), is a distributed, highly-scalable SQL Database that can be run anywhere. With familiar relational models, we deliver the best performance for both transactional and analytical workloads. SingleStore is a scalable SQL database which continuously ingests data to perform operational analysis for your business' front lines. ACID transactions allow you to simultaneously process millions of events per second and analyze billions of rows in relational SQL, JSON geospatial, full-text search, and other formats. SingleStore provides the best data ingestion performance and supports batch loading and real-time data pipelines. SingleStore allows you to query live and historical data with ANSI SQL in a lightning fast manner. You can perform ad-hoc analysis using business intelligence tools, run machine-learning algorithms for real time scoring, and geoanalytic queries in a real time.
  • 2
    Citus Reviews

    Citus

    Citus Data

    $0.27 per hour
    Citus combines the Postgres you know and love with the power of distributed tables. 100% open source. Now with schema-based, row-based, and Postgres 16 support. Scale Postgres using data and queries. You can start off with a single Citus server, then add more nodes and rebalance the shards as you grow. Parallelism, storing more data in memory and using higher I/O bandwidth along with columnar compression can speed up queries by 20x or 300x. Citus is a new extension (not fork) of the latest Postgres version, allowing you to use your familiar SQL toolkit and leverage your Postgres expertise. Use a single database to manage both your analytical and transactional workloads. Download and use Citus Open Source for free. Citus can be managed by you, if you embrace open source and use GitHub. Focus on your app & forget your database. Azure Cosmos DB PostgreSQL for Citus allows you to run your app in the cloud.
  • 3
    Greenplum Reviews

    Greenplum

    Greenplum Database

    Greenplum Database®, an open-source data warehouse, is a fully featured, advanced, and fully functional data warehouse. It offers powerful and fast analytics on petabyte-scale data volumes. Greenplum Database is uniquely designed for big data analytics. It is powered by the most advanced cost-based query optimizer in the world, delivering high analytical query performance with large data volumes. The Apache 2 license is used to release Greenplum Database®. We would like to thank all of our community contributors. We are also open to new contributions. We encourage all contributions to the Greenplum Database community, no matter how small. Open-source, massively parallel data platform for machine learning, analytics, and AI. Rapidly create and deploy models to support complex applications in cybersecurity, predictive management, risk management, fraud detection, among other areas. The fully integrated, open-source analytics platform is now available.
  • 4
    QuestDB Reviews
    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.
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