DBMS > Couchbase vs. Elasticsearch vs. Kinetica vs. Memcached vs. TerminusDB

System Properties Comparison Couchbase vs. Elasticsearch vs. Kinetica vs. Memcached vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

In-memory key-value store, originally intended for caching

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

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

Spatial DBMS
Time Series DBMS

Document store
RDF store

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

www.couchbase.com

www.elastic.co/elasticsearch

www.kinetica.com

www.memcached.org

terminusdb.com

Technical documentation

docs.couchbase.com

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

docs.kinetica.com

github.com/memcached/memcached/wiki

terminusdb.github.io/terminusdb/#

Developer

Couchbase, Inc.

Elastic

Kinetica

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

DataChemist Ltd.

Initial release

2011

2010

2012

2003

2018

Current release

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

8.6, January 2023

7.1, August 2021

1.6.27, May 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

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

Open Source

Elastic License

commercial

Open Source

BSD license

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

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

C, C++

Prolog, Rust

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

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

yes

schema-free

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

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

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

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
ODBC
RESTful HTTP API

Proprietary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

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

yes

user defined functions

yes

Triggers

yes

via the TAP protocol

yes

by using the 'percolation' feature

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

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 or Eventual Consistency depending on configuration

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 journaling

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

yes

GPU vRAM or System RAM

User concepts

Access control

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

Access rights for users and roles on table level

yes

using SASL (Simple Authentication and Security Layer) protocol

Role-based access control

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