DBMS > Bangdb vs. EXASOL vs. JaguarDB vs. Riak KV vs. STSdb

System Properties Comparison Bangdb vs. EXASOL vs. JaguarDB vs. Riak KV vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Performant, highly scalable DBMS for AI and IoT applications

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store
Vector DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

bangdb.com

www.exasol.com

www.jaguardb.com

github.com/STSSoft/STSdb4

Technical documentation

docs.bangdb.com

www.exasol.com/resources

www.jaguardb.com/support.html

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Sachin Sinha, BangDB

Exasol

DataJaguar, Inc.

OpenSource, formerly Basho Technologies

STS Soft SC

Initial release

2012

2000

2015

2009

2011

Current release

BangDB 2.0, October 2021

3.3 July 2023

3.2.0, December 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPL V3.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

the server part. Clients available in other languages

Erlang

Server operating systems

Linux

Linux
OS X

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

primitive types and user defined types (classes)

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

secondary, composite, nested, reverse, geospatial

yes

restricted

SQL

Support of SQL

SQL like support with command line tool

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

HTTP API
Native Erlang Interface

.NET Client API

Supported programming languages

C
C#
C++
Java
Python

Java
Lua
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java

Server-side scripts

Stored procedures

user defined functions

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

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

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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

User concepts

Access control

yes (enterprise version only)

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

rights management via user accounts

yes, using Riak Security

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