Saturday, October 5, 2024

Best Open Source Software List For Data Management In 2024

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Data management software encompasses a range of tools used in collaboration to help businesses collect, store, and maintain data and extract value from it, including everything from data analytics platforms to data warehouses. The best open source tools for data management offer the same features and capabilities as paid versions but are freely available to use, customize, and distribute without being restricted by any proprietary constraints or licensing fees.

As the volume and complexity of enterprise data estates continues to grow, these tools play an increasingly important role in day to day business. We compiled a list of the 19 best open-source data management systems for 2024 to help you better understand the landscape of what tools are available and how they might meet your needs.

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Akeneo Product Information Management (PIM) Community Edition

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Part of Akeneo Product Cloud, Akeno Product Information Management (PIM) Community Edition is an open source data management tool that lets small and medium-sized organizations centralize, manage, enrich, and distribute product information at a low cost. Akeneo is also a product data intelligence tool used to drive multiple-channel product experiences, and a composable SaaS-based solution that optimizes product experiences across owned and unowned channels.

Apache Atlas

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Apache Atlas is an open source platform for metadata and big data governance that empowers data workers across industries. Apache Atlas helps enterprises successfully manage and administer their data resources by letting them create comprehensive catalogs of data assets and powerful categorization and control systems. This allows for better data lineage tracing, metadata discovery, and policy enforcement, resulting in improved data quality, security, and regulatory compliance in Hadoop systems.

Apache Atlas is part of the Apache Software Foundation, an open-source nonprofit organization that creates software products, hardware, communication, and business infrastructure and balances open structure, flexibility, and economic feasibility.

Ataccama ONE

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Ataccama ONE is an AI-powered data management platform that integrates data governance, data quality, and master data management (MDM) into a unified AI-powered fabric. It provides collaborative data enhancement, rapid governance, data discovery, and a marketplace for trustworthy data sets. Ataccama ONE also manages data quality, allowing users to link data sources and apply rules from a customized library, and can detect irregularities in data in real-time. The platform allows you to customize data quality standards, and it supports quick data search and exploration, collaboration, and self-service data onboarding.

Ataccama ONE is user-centric, suited to diverse roles, and intended for mission-critical deployments in highly regulated environments. It provides high availability, comprehensive audit history, and role-based security, and operates natively on common large data platforms such as Spark, AWS Databricks, Hadoop, Hortonworks, Cloudera, MapR, Google, and Azure.

Bloomreach Experience Manager (brXM)

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Bloomreach specializes in open-source data content management software (CMS), and the Bloomreach Experience Manager (brXM) CMS is designed to help e-commerce businesses gather, organize, and analyze customer data. It offers full channel automation, lifecycle intelligence, artificial intelligence-driven predictive analysis, and data management functionality. brXM follows open-source standards and is licensed under Apache Software License 2.0, letting developers access the code through public community git repositories. It includes the Bloomreach Experience Platform dashboard, which lets users access data and application services and create digital experiences from a unified screen.

Cubrid

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Cubrid’s open source database management system software offers a read-and-write performance database system that is stable and scalable and has the high availability required for mission-critical applications. It offers native graphical user interface (GUI)-based admin tools for effective data management, with an emphasis on ease of installation and dependability. Cubrid supports common relational database features that include ACID compliance, query optimization, and comprehensive SQL support. Features include seamless failover during server outages as well as scalability and efficient management of large datasets.

Directus Product Information Management

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Directus Product Information Management system serves as a foundation for effectively managing product catalogs, characteristics, and media. It uses a structured data model to centralize product data across many channels, making it a good fit for e-commerce platforms, digital catalogs, and product information systems. Its features include a flexible data model, backend infrastructure, and frontend specialization, allowing for seamless interaction with diverse frontend applications. Directus is an open-source JavaScript data platform with a powerful API for developers and an easy-to-use app for non-technical users. Operating as both a headless content management system (CMS) and a Backend-as-a-Service (BaaS), the latest update of Directus adds a composable data platform, a real-time API, and an App Dashboard for SQL database management with no limits or data migration needs.

Elasticsearch

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Elasticsearch is one of three components in the ELK stack, along with Logstash and Kibana, and the name is often used to describe the entire ELK stack. Combined, the tools let you aggregate logs from multiple systems and applications, analyze them easily, and create visualizations to help you monitor, troubleshoot, and manage them. Widely used in log management, search engines, monitoring, and security analytics, Elasticsearch is built with Java and uses a NoSQL database that stores unstructured data for full-text search and retrieval. Its distributed architecture, near-real-time indexing, and powerful query digital subscriber line/loop (DSL) provide scalability and versatility.

FirebirdSQL

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FirebirdSQL is an open-source relational database management system maintained as an independent project by a community of C/C++ programmers and technical advisors. Its Initial Developer’s Public License (IDPL) promotes flexibility and accessibility by allowing customizations without imposing download fees, registration, or deployment. Instead, they rely on volunteer funding from its user community. FirebirdSQL is intended to improve data management efficiency by providing features such as a unified graph through its web interface that enables the study of complex dependencies across data ecosystems. The lineage API allows users to programmatically query metadata for tasks such as backfills and root cause analysis as well as gain insights into dataset provenance and global visibility into job runtime and access frequency.

Forest Admin Panel

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The Forest Admin Panel is a low-code SaaS solution that lets businesses connect various apps and data sources into a single customizable open-source data management tool by generating an administrative backend REST API and a user-friendly frontend experience compatible with a variety of technology stacks. Key features include create, read, update, and delete (CRUD) operations, data organization, data visualization, custom business logic, role-based permissions, and collaborative capabilities. The tool is focused on product security and data privacy, which can benefit organizations of all sizes. The plug-and-play admin panel lets developers build apps without code, deploy advanced role management and collaboration systems, and deliver customized tools tailored to the organization’s needs.

GraphDB

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Ontotext’s GraphDB is a highly effective data management system that features full compliance with Resource Description Framework (RDF) 1.1 and SPARQL 1.1 standards. It is built to handle enormous loads, queries, and inferencing in real time, making it ideal for creating knowledge graphs and enterprise-wide data integration and discovery. Features include a highly performant reasoning and query engine, simple deployment, full-text and faceted search, data synchronization to downstream systems, and an easy-to-use high availability cluster based on the Raft consensus algorithm.

GraphDB is notable for its sophisticated features, such as semantic search capabilities, customized reasoning, and seamless integration with RDF4J, which allows developers to work with RDF data easily. Its strong support for standards and protocols enables compatibility with current systems and tools, making it an adaptable option for a variety of industries, including healthcare, banking, and government.

Kylo Data Management

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Kylo Data Management software offers several useful tools for streamlining data management activities. Users benefit from self-service data intake capabilities, which include data cleansing, validation, and profiling features. The software simplifies data preparation with visible SQL and interactive transformations. Data discovery features enable the investigation of data, metadata, lineage, and profile statistics, which improves data comprehension and governance. Monitoring and troubleshooting solutions allow for checking feed health, maintaining SLAs, and effectively fixing performance issues.

Kylo allows the building of batch or streaming pipeline templates with Apache NiFi, allowing users to create sophisticated data pipelines. Kylo’s open-source data lake management software allows for self-service data ingestion and preparation. Used by prominent enterprises globally, including top global brands in industries such as airlines, insurance, telecommunications, financial services, banking, and retail/consumer products, it is enterprise-ready and released under the Apache 2.0 license.

MariaDB

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MariaDB is an open-source relational database management system (RDBMS) that arose as a fork of MySQL following concerns over its purchase by Oracle Corporation. It remains compatible with MySQL while adding new capabilities, improving performance, and encouraging community development. MariaDB supports a variety of storage engines, including Aria, TokuDB, and InnoDB, giving users greater choice in data management and optimization. Its active community and transparent development process add to its stability, security, and constant improvement, making it a popular choice for enterprises and organizations looking for a dependable and scalable database solution.

MariaDB offers various products, including MariaDB Server, a versatile relational database with comprehensive capabilities for data storage, retrieval, and management. MariaDB ColumnStore is an open-source data analytics solution designed for large-scale analytical workloads.

Marquez

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Marquez is an open source metadata management tool that improves data discovery and data lineage management with a variety of capabilities that streamline workflows and optimize data governance processes. It is unified with a visual graph that provides a full picture of data interdependencies, and the flexible lineage API allows for automation activities such as backfills and root cause investigation. Marquez’s data lineage tracking for each pipeline provides global visibility into task runtime and dataset access frequency, facilitating centralized dataset lifecycle management and data quality across the organization.

Marquez is supported by key integrations with popular platforms such as Apache Airflow and Apache Spark and serves as the reference implementation for OpenLineage, encouraging collaboration among the open-source community.

MongoDB Atlas

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MongoDB Atlas is a commercial cloud-based database service that simplifies the management, deployment, and scalability of MongoDB databases. As a fully managed service, MongoDB Atlas manages the intricacies of database administration—including provisioning, monitoring, and backup—allowing developers and organizations to focus on application development rather than infrastructure management. Capabilities include automated scaling for changing workloads, high availability via replica sets and automatic failover, and strong security measures such as network isolation and encrypted data storage.

MongoDB Atlas supports different cloud providers and locations, ensuring deployment flexibility for a wide range of use cases and industries, and offers tools and services for effective data management, including cloud database services designed to handle various data transactions and analytical workloads. The open-source document database is built for easy data development and scaling. It stores data as JSON-like documents with flexible schemas, allowing developers to modify data, apply design techniques, and build applications effortlessly.

MySQL RDBMS

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MySQL Relational Database Management System organizes data into tables with rows and columns for efficient storage and retrieval processing. MySQL supports SQL and allows users to collaborate with the database, execute operations such as data querying, and build table associations. It is known for its speed and efficiency, can manage read-heavy workloads, and can easily scale from small websites to large enterprise applications. Its security mechanism, scalability, data type flexibility, and compatibility with various programming languages and platforms make it a dependable choice for managing data in web applications, content management systems, e-commerce platforms, and other environments backed by an active community and a rich ecosystem of tools and plugins.

MySQL also offers a wide range of products, such as a fully managed MySQL Database Service, MySQL Enterprise Edition, and the free MySQL Community Edition. In addition, MySQL Cluster provides distributed database capabilities for high availability, while MySQL Workbench and MySQL Router provide visual tools and transparent routing.

Oracle Modern Data Platform

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Oracle Modern Data Platform is a comprehensive solution that simplifies the entire data lifecycle and delivers faster insights. It applies to the full data stack, including transactional, warehousing, analytical, and AI/ML assets. The platform is open source and modular, allowing organizations to deploy workloads with greater flexibility and seamless interaction. It provides intelligent insights by combining data and embedded intelligence. Use cases are diverse, ranging from financial services and healthcare to retail, the public sector, manufacturing, and communications. It is based on Oracle Cloud Infrastructure (OCI) and offers scalability, compliance, security, and tailored data services.

Pimcore

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Pimcore’s MDM and PIM features consolidate and manage a company’s master and product data, allowing for the development of sophisticated data models while guaranteeing data quality and control. Pimcore takes an API-based approach, allowing for simple integration to third-party systems using PHP and REST APIs. The administration interface is built on Sencha’s Ext-JS-6 development framework. Pimcore’s PIM platform centralizes marketing, sales, and technical product information, providing flexibility in data modeling. Its web-based user interface and context-sensitive drag-and-drop functionality make dealing with product information more efficient.

Pimcore is a well-known developer of open-source software solutions that specialize in data management and user experience enhancement. Its software enables omnichannel publication and syndication, and its API-driven design integrates effortlessly with third-party applications.

PostgreSQL

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PostgreSQL is an open-source relational database management system known for its flexibility and dependability, letting users edit, manipulate, and visualize data. PostgreSQL’s open source community is constantly delivering novel solutions that maintain compatibility with all major operating systems and atomicity, consistency, isolation, and durability (ACID) compliance. Developers can quickly design apps using the agileBase platform, while PostgreSQL offers data safety, security, and scalability at the software stack’s core. With a diverse set of interfaces, extensions, and software tools from different open-source groups, organizations, and individuals, PostgreSQL meets a wide range of needs in administration, development, clustering, replication, and reporting.

Quilt

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Quilt is Amazon Web Services’ (AWS) open-source data management solution that converts scattered, unlabeled data into replicable, discoverable, and trustworthy datasets. It includes a Python API for producing and maintaining datasets, a web catalog for exploring, and backend services for orchestration. Quilt is frequently used in scientific research, speeding up product development and ensuring data integrity through versioning—Tessera Therapeutics and Celsius Therapeutics are two notable case studies. It is a cloud computing platform that provides support for a variety of open-source databases while also actively contributing to the community. With over 15 purpose-built database engines, AWS enables enterprises and developers to create, deploy, and manage cloud-based applications and data infrastructure.

Bottom Line: Open Source Software Simplifies Data Management

Using open-source software for data management can streamline business operations and improve efficiency. Across industries, handling large amounts of data is important for making informed business decisions. Open-source solutions—including those for data management—enable businesses and developers to tailor their data management systems to their specific requirements, assuring flexibility, scalability, and cost-effectiveness.

Read about the benefits of data management, learn why it’s important for enterprises and what the best practices are, see what our experts think it will look like in the future, or browse through our reviews and recommendations for the best data management tools.

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