DBMS > Datastax Enterprise vs. Derby vs. Ignite vs. PostgreSQL vs. TDengine
System Properties Comparison Datastax Enterprise vs. Derby vs. Ignite vs. PostgreSQL vs. TDengine
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Name | Datastax Enterprise Xexclude from comparison | Derby often called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB Xexclude from comparison | Ignite Xexclude from comparison | PostgreSQL Xexclude from comparison | TDengine Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform. | Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server. | Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Time Series DBMS and big data platform | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Wide column store | Relational DBMS | Key-value store Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.datastax.com/products/datastax-enterprise | db.apache.org/derby | ignite.apache.org | www.postgresql.org | github.com/taosdata/TDengine tdengine.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.datastax.com | db.apache.org/derby/manuals/index.html | apacheignite.readme.io/docs | www.postgresql.org/docs | docs.tdengine.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | DataStax | Apache Software Foundation | Apache Software Foundation | PostgreSQL Global Development Group www.postgresql.org/developer | TDEngine, previously Taos Data | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2011 | 1997 | 2015 | 1989 1989: Postgres, 1996: PostgreSQL | 2019 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 6.8, April 2020 | 10.17.1.0, November 2023 | Apache Ignite 2.6 | 16.3, May 2024 | 3.0, August 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Apache version 2 | Open Source Apache 2.0 | Open Source BSD | Open Source AGPL V3, also commercial editions available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | Java | C++, Java, .Net | C | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X | All OS with a Java VM | Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | yes | yes | yes specific XML-type available, but no XML query functionality. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like DML and DDL statements (CQL); Spark SQL | yes | ANSI-99 for query and DML statements, subset of DDL | yes standard with numerous extensions | Standard SQL with extensions for time-series applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | JDBC | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | ADO.NET JDBC native C library ODBC streaming API for large objects | JDBC RESTful HTTP API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | Java | C# C++ Java PHP Python Ruby Scala | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Go Java JavaScript (Node.js) PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | Java Stored Procedures | yes (compute grid and cache interceptors can be used instead) | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes | yes (cache interceptors and events) | yes | yes, via alarm monitoring | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | none | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | configurable replication factor, datacenter aware, advanced replication for edge computing | Source-replica replication | yes (replicated cache) | Source-replica replication other methods possible by using 3rd party extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | yes (compute grid and hadoop accelerator) | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | ACID | ACID | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per object | fine grained access rights according to SQL-standard | Security Hooks for custom implementations | fine grained access rights according to SQL-standard | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Datastax Enterprise | Derby often called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB | Ignite | PostgreSQL | TDengine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | TDengine™ is a next generation data historian purpose-built for Industry 4.0 and... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Supporting the following application requirements: Zero downtime - Built on Apache... » more | High Performance at any Scale: TDengine is purpose-built for handling massive industrial... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Applications that must be massively and linearly scalable with 100% uptime and able... » more | TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Annual subscription » more | TDengine OSS is an open source, cloud native time series database. It includes built-in... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Seamless Data Integration from MQTT and InfluxDB to TDengine Solving Long Query Performance Bottlenecks What Is Predictive Maintenance? Can Typical Time-Series Databases Replace Data Historians? TDengine 3.3.0.0 Release Notes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Datastax Enterprise | Derby often called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB | Ignite | PostgreSQL | TDengine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | DataStax previews new Hyper Converged Data Platform for enterprise AI DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite ... DataStax Rolls Out Vector Search for Astra DB to Support Gen AI DataStax announces vector search capabilities in its on-prem Apache Cassandra database DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers provided by Google News | JDBC tutorial: Easy installation and setup with Apache Derby The Arrival of Java 20 Installing Apache Hive 3.1.2 on Windows 10 | by Hadi Fadlallah The Apache® Software Foundation Announces 18 Years of Open Source Leadership No, Citrix did not kill CloudStack provided by Google News | GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 Apache Ignite: An Overview What is Apache Ignite? How is Apache Ignite Used? Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services Fire up big data processing with Apache Ignite provided by Google News | Deep PostgreSQL Thoughts: Valuing Currency EDB unveils EDB Postgres AI At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Automatically Generate Types for Your PostgreSQL Database provided by Google News | TDengine named Top Global Industrial Data Management Solution New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB TDengine debuts cloud-based time-series data processing platform for IoT deployments Comparing Different Time-Series Databases MindsDB is now the leading and fastest growing applied ML platform in the world India - English provided by Google News |
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