DBMS > Citus vs. Elasticsearch

System Properties Comparison Citus vs. Elasticsearch

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Editorial information provided by DB-Engines
Name	Citus  Xexclude from comparison	Elasticsearch  Xexclude from comparison
Description	Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL	A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric
Primary database model	Relational DBMS	Search engine
Secondary database models	Document store	Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 1.74 Rank #133   Overall #65   Relational DBMS	Score 156.00 Rank #8   Overall #1   Search engines
Website	www.citusdata.com	www.elastic.co/­elasticsearch
Technical documentation	docs.citusdata.com	www.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
Developer		Elastic
Initial release	2010	2010
Current release	8.1, December 2018	7.8.0, June 2020
License Commercial or Open Source	Open Source AGPL, commercial license also available	Open Source Elastic License
Cloud-based only Only available as a cloud service	no	no
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Implementation language	C	Java
Server operating systems	Linux	All OS with a Java VM
Data scheme	yes	schema-free Flexible type definitions. Once a type is defined, it is persistent
Typing predefined data types such as float or date	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.	yes specific XML type available, but no XML query functionality	no
Secondary indexes	yes	yes All search fields are automatically indexed
SQL Support of SQL	yes standard, with numerous extensions	SQL-like query language
APIs and other access methods	ADO.NET JDBC native C library ODBC streaming API for large objects	Java API RESTful HTTP/JSON API
Supported programming languages	.Net C C++ Delphi Java JavaScript (Node.js) Perl PHP Python Tcl	.Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby
Server-side scripts Stored procedures	user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.	yes
Triggers	yes	yes by using the 'percolation' feature
Partitioning methods Methods for storing different data on different nodes	Sharding	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	Source-replica replication other methods possible by using 3rd party extensions	yes
MapReduce Offers an API for user-defined Map/Reduce methods	no	ES-Hadoop Connector
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys Referential integrity	yes	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	no
Concurrency Support for concurrent manipulation of data	yes	yes
Durability Support for making data persistent	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	no	Memcached and Redis integration
User concepts Access control	fine grained access rights according to SQL-standard
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	Citus	Elasticsearch
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