DBMS > Apache Impala vs. Riak KV vs. STSdb vs. Transbase

System Properties Comparison Apache Impala vs. Riak KV vs. STSdb vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key-value store

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

Key-value store

Relational DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

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

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

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

impala.apache.org

github.com/STSSoft/STSdb4

www.transaction.de/en/products/transbase.html

Technical documentation

impala.apache.org/impala-docs.html

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

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

OpenSource, formerly Basho Technologies

STS Soft SC

Transaction Software GmbH

Initial release

2013

2009

2011

1987

Current release

4.1.0, June 2022

3.2.0, December 2022

4.0.8, September 2015

Transbase 8.3, 2022

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 development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

C and C++

Server operating systems

Linux

Linux
OS X

Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

HTTP API
Native Erlang Interface

.NET Client API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

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
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes, using Riak Security

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

Riak NoSQL Database: Use Cases and Best Practices
23 December 2011, InfoQ.com

Basho, Maker of Riak NoSQL Database, Raises $25M
13 January 2015, Data Center Knowledge

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

NoSQL pioneer Basho stamps its mark on time stamp data with Riak TS
6 October 2015, The Register

provided by Google News

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