DBMS > Apache Impala vs. CouchDB vs. eXtremeDB vs. GraphDB vs. PostgreSQL
System Properties Comparison Apache Impala vs. CouchDB vs. eXtremeDB vs. GraphDB vs. PostgreSQL
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Name | Apache Impala Xexclude from comparison | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" Xexclude from comparison | eXtremeDB Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Analytic DBMS for Hadoop | A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones. | Natively in-memory DBMS with options for persistency, high-availability and clustering | Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Document store | Relational DBMS Time Series DBMS | Graph DBMS RDF store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store | Spatial DBMS using the Geocouch extension | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | impala.apache.org | couchdb.apache.org | www.mcobject.com | www.ontotext.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | impala.apache.org/impala-docs.html | docs.couchdb.org/en/stable | www.mcobject.com/docs/extremedb.htm | graphdb.ontotext.com/documentation | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | Apache Software Foundation Apache top-level project, originally developed by Cloudera | Apache Software Foundation Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer | McObject | Ontotext | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2005 | 2001 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 4.1.0, June 2022 | 3.3.3, December 2023 | 8.2, 2021 | 10.4, October 2023 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2 | Open Source Apache version 2 | commercial | commercial Some plugins of GraphDB Workbench are open sourced | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | Erlang | C and C++ | Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Android BSD Linux OS X Solaris Windows | AIX HP-UX Linux macOS Solaris Windows | All OS with a Java VM Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | yes | schema-free and OWL/RDFS-schema support; RDF shapes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | no | 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 | no | no support of XML interfaces available | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes via views | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like DML and DDL statements | no | yes with the option: eXtremeSQL | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC ODBC | RESTful HTTP/JSON API | .NET Client API JDBC JNI ODBC Proprietary protocol RESTful HTTP API | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | All languages supporting JDBC/ODBC | C C# ColdFusion Erlang Haskell Java JavaScript Lisp Lua Objective-C OCaml Perl PHP PL/SQL Python Ruby Smalltalk | .Net C C# C++ Java Lua Python Scala | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes user defined functions and integration of map-reduce | View functions in JavaScript | yes | well-defined plugin interfaces; JavaScript server-side extensibility | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | yes by defining events | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding improved architecture with release 2.0 | horizontal partitioning / sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor | Multi-source replication Source-replica replication | Active Replication Fabric™ for IoT Multi-source replication by means of eXtremeDB Cluster option Source-replica replication by means of eXtremeDB High Availability option | Multi-source replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes query execution via MapReduce | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency | Eventual Consistency | Immediate Consistency | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes | yes Constraint checking | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no atomic operations within a single document possible | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes strategy: optimistic locking | yes Optimistic (MVCC) and pessimistic (locking) strategies available | 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. | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users, groups and roles based on Apache Sentry and Kerberos | Access rights for users can be defined per database | Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on. | fine grained access rights according to SQL-standard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache Impala | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" | eXtremeDB | GraphDB former name: OWLIM | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small... » more | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | eXtremeDB databases can be modeled relationally or as objects and can utilize SQL... » more | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,... » more | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,... » more | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | With hundreds of customers and over 30 million devices/applications using the product... » more | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | For server use cases, there is a simple per-server license irrespective of the number... » more | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Okay, RAG… We Have a Problem Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP How Knowledge Graphs Power Data Mesh and Data Fabric Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI Using GraphDB’s Natural Language Interface to Talk with Your Content | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache Impala | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" | eXtremeDB | GraphDB former name: OWLIM | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | 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 Monitoring PostgreSQL with Redgate Monitor Cloudera creates observability tool to help enterprises manage cloud costs Apache Impala becomes Top-Level Project Cloudera Bringing Impala to AWS Cloud Apache Doris just 'graduated': Why care about this SQL data warehouse Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop provided by Google News How to Automate A Blog Post App Deployment With GitHub Actions, Node.js, CouchDB, and Aptible How to install the CouchDB NoSQL database on Debian Server 11 IBM Cloudant pulls plan to fund new foundational layer for CouchDB CouchDB 3.0 ends admin party era • DEVCLASS CouchDB 3.0 puts safety first provided by Google News McObject Announces the Release of eXtremeDB/rt 1.2 McObject Announces Availability of eXtremeDB/rt for Green Hills Software's INTEGRITY RTOS McObject Announces Availability of eXtremeDB/rt for Microsoft Azure RTOS ThreadX Latest embedded DBMS supports asymmetric multiprocessing systems With eXtremeDB Database, Spreadbrokers Targets Real-Time Trading provided by Google News Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace Ontotext Unveils GraphDB 10.4 with Enhanced AWS Integration and ChatGPT Connector Ontotext GraphDB is available on Azure, delivers rich knowledge graph experience Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released It's just semantics: Bulgarian software dev Ontotext squeezes out GraphDB 9.1 provided by Google News Automatically Generate Types for Your PostgreSQL Database Baffle Delivers Enterprise-Grade Data Security for PostgreSQL on Amazon RDS and Amazon Aurora Why PostgreSQL Is the Bedrock for the Future of Data Crunchy Data Introduces Postgres Query Engine for Data Lakes, Crunchy Bridge for Analytics Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need provided by Google News |
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