DBMS > Apache Druid vs. Apache Impala vs. Couchbase vs. JaguarDB vs. PostgreSQL
System Properties Comparison Apache Druid vs. Apache Impala vs. Couchbase vs. JaguarDB vs. PostgreSQL
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Name | Apache Druid Xexclude from comparison | Apache Impala Xexclude from comparison | Couchbase Originally called Membase Xexclude from comparison | JaguarDB Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data | Analytic DBMS for Hadoop | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Performant, highly scalable DBMS for AI and IoT applications | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS Time Series DBMS | Relational DBMS | Document store | Key-value store Vector DBMS | 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 | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extension Search engine Time Series DBMS Vector DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | druid.apache.org | impala.apache.org | www.couchbase.com | www.jaguardb.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | druid.apache.org/docs/latest/design | impala.apache.org/impala-docs.html | docs.couchbase.com | www.jaguardb.com/support.html | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation and contributors | Apache Software Foundation Apache top-level project, originally developed by Cloudera | Couchbase, Inc. | DataJaguar, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2013 | 2011 | 2015 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 29.0.1, April 2024 | 4.1.0, June 2022 | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 3.3 July 2023 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache license v2 | Open Source Apache Version 2 | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source GPL V3.0 | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | C++ | C, C++, Go and Erlang | C++ the server part. Clients available in other languages | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Unix | Linux | Linux OS X Windows | Linux | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes schema-less columns are supported | yes | schema-free | 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 | no | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL for querying | SQL-like DML and DDL statements | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | A subset of ANSI SQL is implemented but no views, foreign keys, triggers | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC RESTful HTTP/JSON API | JDBC ODBC | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Clojure JavaScript PHP Python R Ruby Scala | All languages supporting JDBC/ODBC | .Net C Go Java JavaScript Node.js Kotlin PHP Python Ruby Scala | C C++ Go 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 | no | yes user defined functions and integration of map-reduce | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes via the TAP protocol | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding manual/auto, time-based | Sharding | Automatic Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes, via HDFS, S3 or other storage engines | selectable replication factor | Multi-source replication including cross data center replication Source-replica replication | Multi-source replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes query execution via MapReduce | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Eventual Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no | ACID | no | 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. | no | no | yes Ephemeral buckets | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system | Access rights for users, groups and roles based on Apache Sentry and Kerberos | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | rights management via user accounts | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache Druid | Apache Impala | Couchbase Originally called Membase | JaguarDB | 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 Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers 'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers Apache Druid Takes Its Place In The Pantheon Of Databases How to connect DataGrip to Apache Druid | by Zisis Flokas provided by Google News 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 Updates & Upserts in Hadoop Ecosystem with Apache Kudu provided by Google News A Closer Look at 9 Analyst Recommendations For Couchbase Database company Couchbase cruises to another solid earnings and revenue beat Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers Couchbase, Inc. (NASDAQ:BASE) Shares Slammed 29% But Getting In Cheap Might Be Difficult Regardless Couchbase (NASDAQ:BASE) Price Target Lowered to $30.00 at DA Davidson provided by Google News PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News |
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