DBMS > eXtremeDB vs. OushuDB vs. SAP HANA vs. SingleStore

System Properties Comparison eXtremeDB vs. OushuDB vs. SAP HANA vs. SingleStore

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Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Website

www.mcobject.com

www.oushu.com/product/oushuDB

www.sap.com/products/hana.html

www.singlestore.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

www.oushu.com/documentation

help.sap.com/hana

docs.singlestore.com

Developer

McObject

Oushu

SAP

SingleStore Inc.

Initial release

2001

2010

2013

Current release

8.2, 2021

4.0.1, August 2020

2.0 SPS07 (April 4, 2023), April 2023

8.5, January 2024

License

Commercial or Open Source

commercial

free developer edition available

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C and C++

C++, Go

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Appliance or cloud-service

Linux

64 bit version required

Data 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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

Full-featured ANSI SQL support

yes

but no triggers and foreign keys

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

C
C++

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

Server-side scripts

Stored procedures

yes

SQLScript, R

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

yes

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

yes, multi-version concurrency control (MVCC)

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.

In-memory capabilities

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

yes

User concepts

Access control

Kerberos, SSL and role based access

yes

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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F ree Tier and Enterprise Edition
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