DBMS > Oracle vs. SingleStore vs. SpaceTime vs. Splice Machine vs. TimesTen

System Properties Comparison Oracle vs. SingleStore vs. SpaceTime vs. Splice Machine vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

SpaceTime is a spatio-temporal DBMS with a focus on performance.

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

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Relational DBMS

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

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.oracle.com/database

www.singlestore.com

www.mireo.com/spacetime

splicemachine.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.oracle.com/en/database

docs.singlestore.com

splicemachine.com/how-it-works

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Oracle

SingleStore Inc.

Mireo

Splice Machine

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1980

2013

2020

2014

1998

Current release

23c, September 2023

8.5, January 2024

3.1, March 2021

Release 22.1

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free developer edition available

commercial

Open Source

AGPL 3.0, commercial license available

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

C and C++

C++, Go

C++

Java

Server operating systems

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

64 bit version required

Linux

Linux
OS X
Solaris
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

Schemaless in JSON and XML columns

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

SQL

Support of SQL

yes

with proprietary extensions

yes

but no triggers and foreign keys

A subset of ANSI SQL is implemented

yes

APIs and other access methods

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Bash
C
C#
Java
JavaScript (Node.js)
Python

C#
C++
Python

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

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

Java

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

hash partitioning

Fixed-grid hypercubes

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Real-time block device replication (DRBD)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

can define user-defined aggregate functions for map-reduce-style calculations

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

yes

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

fine grained access rights according to SQL-standard

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