DBMS > Couchbase vs. Elasticsearch vs. RocksDB vs. TypeDB

System Properties Comparison Couchbase vs. Elasticsearch vs. RocksDB vs. TypeDB

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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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Search engine

Key-value store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

www.couchbase.com

www.elastic.co/elasticsearch

rocksdb.org

typedb.com

Technical documentation

docs.couchbase.com

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

github.com/facebook/rocksdb/wiki

typedb.com/docs

Developer

Couchbase, Inc.

Elastic

Facebook, Inc.

Vaticle

Initial release

2011

2010

2013

2016

Current release

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

8.6, January 2023

9.2.1, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

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

Open Source

Elastic License

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

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++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

schema-free

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

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

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

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

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
C++
Go
Java
Perl
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

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

yes

Triggers

yes

via the TAP protocol

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

yes

by using Apache Kafka and Apache Zookeeper

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

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

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

ACID

yes

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

yes

User concepts

Access control

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

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
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Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
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