DBMS > Axibase vs. Bangdb vs. Hypertable vs. Riak KV

System Properties Comparison Axibase vs. Bangdb vs. Hypertable vs. Riak KV

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Distributed, fault tolerant key-value store

Primary database model

Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Wide column store

Key-value store

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

Secondary database models

Spatial DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

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

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

axibase.com/docs/atsd/finance

bangdb.com

Technical documentation

docs.bangdb.com

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

Developer

Axibase Corporation

Sachin Sinha, BangDB

Hypertable Inc.

OpenSource, formerly Basho Technologies

Initial release

2013

2012

2009

Current release

15585

BangDB 2.0, October 2021

0.9.8.11, March 2016

3.2.0, December 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

BSD 3

Open Source

GNU version 3. Commercial license available

Open Source

Apache version 2, commercial enterprise edition

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

Java

C, C++

C++

Erlang

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

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

restricted

only exact value or prefix value scans

restricted

SQL

Support of SQL

SQL-like query language

SQL like support with command line tool

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Proprietary protocol
RESTful HTTP API

C++ API
Thrift

HTTP API
Native Erlang Interface

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Java
Python

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

selectable replication factor on file system level

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

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

User concepts

Access control

yes (enterprise version only)

yes, using Riak Security

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