DBMS > Citus vs. Couchbase vs. Elasticsearch vs. GeoSpock vs. Tibero

System Properties Comparison Citus vs. Couchbase vs. Elasticsearch vs. GeoSpock vs. Tibero

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

Spatial and temporal data processing engine for extreme data scale

A secure RDBMS, designed for easy portability from Oracle

Primary database model

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
Spatial DBMS
Vector DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

www.citusdata.com

www.couchbase.com

www.elastic.co/elasticsearch

geospock.com

us.tmaxsoft.com/products/tibero

Technical documentation

docs.citusdata.com

docs.couchbase.com

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Couchbase, Inc.

Elastic

GeoSpock

TmaxSoft

Initial release

2010

2011

2010

2003

Current release

8.1, December 2018

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

8.6, January 2023

2.0, September 2019

6, April 2015

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Elastic License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

Java

Java, Javascript

C and Assembler

Server operating systems

Linux

Linux
OS X
Windows

All OS with a Java VM

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

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

yes

Secondary indexes

yes

All search fields are automatically indexed

temporal, categorical

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Java API
RESTful HTTP/JSON API

JDBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Persistent Stored Procedure (PSM)

Triggers

yes

via the TAP protocol

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

Sharding

Automatic sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

including cross data center replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

Memcached and Redis integration

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users can be defined per table

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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