DBMS > HBase vs. Riak KV vs. STSdb vs. Transwarp Hippo vs. Yanza

System Properties Comparison HBase vs. Riak KV vs. STSdb vs. Transwarp Hippo vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Time Series DBMS for IoT Applications

Primary database model

Wide column store

Key-value store

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

Key-value store

Vector DBMS

Time Series DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

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

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

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

hbase.apache.org

github.com/STSSoft/STSdb4

www.transwarp.cn/en/subproduct/hippo

yanza.com

Technical documentation

hbase.apache.org/book.html

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

OpenSource, formerly Basho Technologies

STS Soft SC

Yanza

Initial release

2008

2009

2011

2023

2015

Current release

2.3.4, January 2021

3.2.0, December 2022

4.0.8, September 2015

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
OS X

Windows

Linux
macOS

Windows

Data scheme

schema-free, schema definition possible

schema-free

yes

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

primitive types and user defined types (classes)

Vector, Numeric and String

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

restricted

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
Thrift

HTTP API
Native Erlang Interface

.NET Client API

RESTful HTTP API

HTTP API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
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

C++
Java
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate 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

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes, using Riak Security

Role based access control and fine grained access rights

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More resources

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