DBMS > Riak TS vs. SAP HANA vs. Splice Machine vs. UniData,UniVerse

System Properties Comparison Riak TS vs. SAP HANA vs. Splice Machine vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

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

In-memory, column based data store. Available as appliance or cloud service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Time Series DBMS

Relational DBMS

Multivalue DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

www.sap.com/products/hana.html

splicemachine.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

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

help.sap.com/hana

splicemachine.com/how-it-works

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Open Source, formerly Basho Technologies

SAP

Splice Machine

Rocket Software

Initial release

2015

2010

2014

1985

Current release

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

commercial

Open Source

AGPL 3.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Erlang

Java

Server operating systems

Linux
OS X

Appliance or cloud-service

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

HTTP API
Native Erlang Interface

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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++
Java
JavaScript (Node.js)
Python
R
Scala

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Erlang

SQLScript, R

yes

Java

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

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

Access rights according to SQL-standard and operating system based

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