DBMS > EXASOL vs. GigaSpaces vs. SAP HANA vs. SQream DB

System Properties Comparison EXASOL vs. GigaSpaces vs. SAP HANA vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

www.exasol.com

www.gigaspaces.com

www.sap.com/products/hana.html

sqream.com

Technical documentation

www.exasol.com/resources

docs.gigaspaces.com/latest/landing.html

help.sap.com/hana

docs.sqream.com

Developer

Exasol

Gigaspaces Technologies

SAP

SQream Technologies

Initial release

2000

2010

2017

Current release

15.5, September 2020

2.0 SPS07 (April 4, 2023), April 2023

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses 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

Java, C++, .Net

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
macOS
Solaris
Windows

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

.Net
C++
Java
Python
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

SQLScript, R

user defined functions in Python

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

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

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

Role-based access control

yes

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