DBMS > Kdb vs. Riak TS vs. RocksDB vs. SiteWhere vs. Teradata

System Properties Comparison Kdb vs. Riak TS vs. RocksDB vs. SiteWhere vs. Teradata

Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

M2M integration platform for persisting/querying time series data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

kx.com

rocksdb.org

github.com/sitewhere/sitewhere

www.teradata.com

Technical documentation

code.kx.com

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

github.com/facebook/rocksdb/wiki

sitewhere1.sitewhere.io/index.html

docs.teradata.com

Developer

Kx Systems, a division of First Derivatives plc

Open Source, formerly Basho Technologies

Facebook, Inc.

SiteWhere

Teradata

Initial release

2000

kdb was released 2000, kdb+ in 2003

2015

2013

2010

1984

Current release

3.6, May 2018

3.0.0, September 2022

8.11.4, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

commercial

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

Erlang

C++

Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X

Linux

Linux
OS X
Windows

hosted
Linux

Data scheme

yes

schema-free

predefined scheme

yes

Typing

predefined data types such as float or date

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

table attribute 'grouped'

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like query language (q)

yes, limited

yes

SQL 2016 + extensions

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP API
Native Erlang Interface

C++ API
Java API

HTTP REST

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

Erlang

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

with views

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Sharding

based on HBase

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

yes

ACID

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

rights management via user accounts

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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