DBMS > Couchbase vs. IBM Db2 Event Store vs. Sadas Engine vs. Sequoiadb vs. TerminusDB

System Properties Comparison Couchbase vs. IBM Db2 Event Store vs. Sadas Engine vs. Sequoiadb 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

Distributed Event Store optimized for Internet of Things use cases

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

NewSQL database with distributed OLTP and SQL

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

Primary database model

Document store

Event Store
Time Series DBMS

Relational DBMS

Document store
Relational DBMS

Graph DBMS

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
RDF store

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

www.couchbase.com

www.ibm.com/products/db2-event-store

www.sadasengine.com

www.sequoiadb.com

terminusdb.com

Technical documentation

docs.couchbase.com

www.ibm.com/docs/en/db2-event-store

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

terminusdb.github.io/terminusdb/#

Developer

Couchbase, Inc.

IBM

SADAS s.r.l.

Sequoiadb Ltd.

DataChemist Ltd.

Initial release

2011

2017

2006

2013

2018

Current release

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

2.0

8.0

11.0.0, January 2023

License

Commercial or Open Source

Open Source

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

commercial

free developer edition available

commercial

free trial version available

Open Source

Server: AGPL; Client: Apache V2

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

C and C++

C++

Prolog, Rust

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

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

yes

through the embedded Spark runtime

yes

SQL-like query language

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

proprietary protocol using JSON

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
C++
Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

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

yes

JavaScript

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

horizontal partitioning

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Active-active shard replication

none

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

yes

managed by 'Learn by Usage'

User concepts

Access control

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

simple password-based access control

Role-based access control

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