DBMS > Bangdb vs. BigchainDB vs. Couchbase vs. IBM Db2 Event Store vs. Kdb

System Properties Comparison Bangdb vs. BigchainDB vs. Couchbase vs. IBM Db2 Event Store vs. Kdb

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

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

High performance Time Series DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Event Store
Time Series DBMS

Time Series DBMS
Vector DBMS

Secondary database models

Spatial DBMS

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

Relational DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	16.59
Rank	#36	Overall
	#5	Document stores

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

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Website

bangdb.com

www.bigchaindb.com

www.couchbase.com

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

kx.com

Technical documentation

docs.bangdb.com

bigchaindb.readthedocs.io/en/latest

docs.couchbase.com

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

code.kx.com

Developer

Sachin Sinha, BangDB

Couchbase, Inc.

IBM

Kx Systems, a division of First Derivatives plc

Initial release

2012

2016

2011

2017

2000

kdb was released 2000, kdb+ in 2003

Current release

BangDB 2.0, October 2021

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

2.0

3.6, May 2018

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL v3

Open Source

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

commercial

free developer edition available

commercial

free 32-bit version

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++

Python

C, C++, Go and Erlang

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

table attribute 'grouped'

SQL

Support of SQL

SQL like support with command line tool

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

yes

through the embedded Spark runtime

SQL-like query language (q)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
RESTful HTTP API

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Supported programming languages

C
C#
C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

.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

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Server-side scripts

Stored procedures

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

yes

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

via the TAP protocol

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Automatic Sharding

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

Multi-source replication

including cross data center replication
Source-replica replication

Active-active shard replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

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, optimistic concurrency control

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes,with MongoDB ord RethinkDB

yes

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

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

Ephemeral buckets

yes

User concepts

Access control

yes (enterprise version only)

yes

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

fine grained access rights according to SQL-standard

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.