DBMS > BigchainDB vs. Cachelot.io vs. Couchbase vs. IBM Db2 vs. TDSQL for MySQL

System Properties Comparison BigchainDB vs. Cachelot.io vs. Couchbase vs. IBM Db2 vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

In-memory caching system

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational 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

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

www.bigchaindb.com

cachelot.io

www.couchbase.com

www.ibm.com/products/db2

www.tencentcloud.com/products/dcdb

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.couchbase.com

www.ibm.com/docs/en/db2

www.tencentcloud.com/document/product/1042

Developer

Couchbase, Inc.

IBM

Tencent

Initial release

2016

2015

2011

1983

host version

2013

Current release

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

12.1, October 2016

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Simplified BSD License

Open Source

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

commercial

free version is available

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

Python

C++

C, C++, Go and Erlang

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Data scheme

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

SQL

Support of SQL

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

yes

APIs and other access methods

CLI Client
RESTful HTTP API

Memcached protocol

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

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

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic Sharding

Sharding

only with Windows/Unix/Linux Version

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication

including cross data center replication
Source-replica replication

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

yes

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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