Compare the Top Relational Database for Linux as of June 2025

What is Relational Database for Linux?

Relational database software provides users with the tools to capture, store, search, retrieve and manage information in data points related to one another. Compare and read user reviews of the best Relational Database for Linux currently available using the table below. This list is updated regularly.

  • 1
    KS DB Merge Tools

    KS DB Merge Tools

    KS DB Merge Tools

    KS DB Merge Tools is an easy to use diff & merge tool for MySQL, MariaDB, Oracle Database, SQL Server, PostgreSQL, SQLite, MS Access 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.
    Starting Price: $65
  • 2
    Tibero

    Tibero

    TmaxSoft

    Tibero is a relational model-based standard DBMS that has been developed with stable architecture that requires minimal resources from the design step. It allows to efficiently respond to big data processing requests from massive sessions. In addition, it provides a flexible and user-friendly development and easy operating environment based on standards and compatibility. - Multi-Process, multi-thread architecture and various data processing technologies, which support reliable and effective resource management and rapidly process multi-user requests. 1. Shared-disk based active clustering that assures high availability and reliability. 2. Development environment compatibility in compliance with standards.
  • 3
    IBM Cloud SQL Query
    Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.
    Starting Price: $5.00/Terabyte-Month
  • 4
    Apache Phoenix

    Apache Phoenix

    Apache Software Foundation

    Apache Phoenix enables OLTP and operational analytics in Hadoop for low-latency applications by combining the best of both worlds. The power of standard SQL and JDBC APIs with full ACID transaction capabilities and the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store. Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. Become the trusted data platform for OLTP and operational analytics for Hadoop through well-defined, industry-standard APIs. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows.
    Starting Price: Free
  • 5
    IBM Informix
    IBM Informix® is a fast and flexible database with the ability to seamlessly integrate SQL, NoSQL/JSON, and time series and spatial data. Its versatility and ease of use make Informix a preferred solution for a wide range of environments, from enterprise data warehouses to individual application development. Also, with its small footprint and self-managing capabilities, Informix is well suited for embedded data-management solutions. IoT data demands robust processing and integration capabilities. Informix offers a hybrid database system with minimal administrative requirements and memory footprint combined with powerful functionality. Key features make Informix ideal for multi-tiered architectures that require processing at the device level, at gateway layers and in the cloud. Native encryption to protect data at rest and in motion. Support for flexible schema, multiple APIs and configurations.
  • 6
    CrateDB

    CrateDB

    CrateDB

    The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data.
  • 7
    Gilhari

    Gilhari

    Software Tree

    We’re thrilled to announce that Software Tree has won a 2021 DEVIES Award in the code frameworks/libraries category for its innovative Gilhari microservice framework. Gilhari makes it easy for developers to quickly develop high-performance, database-agnostic, and Docker-compatible RESTful applications that need to interact with JSON data in cloud or on-premises. The object-oriented world and the relational world are conceptually different. Manually writing the verbose mapping logic to bridge the gap between the object-oriented and relational artifacts is tedious and time-consuming. Software Tree’s ORM technology frameworks are lightweight in their design and implementation and provide a lightweight feel in their usage. The lightweight aspects of our ORM technology do not compromise on its power and functionality, though. This results in faster development and deployment of modern applications that require flexible object-oriented access to relational data.
  • 8
    rqlite

    rqlite

    rqlite

    The lightweight, user-friendly, distributed relational database built on SQLite. Fault tolerance and high availability with zero hassle. rqlite is a distributed relational database that combines the simplicity of SQLite with the robustness of a fault-tolerant, highly available system. It's developer-friendly, its operation is straightforward, and it's designed for reliability with minimal complexity. Deploy in seconds, with no complex configurations. Seamlessly integrates with modern cloud infrastructures. Built on SQLite, the world’s most popular database. Supports full-text search, Vector Search, and JSON documents. Access controls and encryption for secure deployments. Rigorous, automated testing ensures high quality. Clustering provides high availability and fault tolerance. Automatic node discovery simplifies clustering.
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