DBMS > GBase vs. HyperSQL vs. Ignite vs. Microsoft Azure Synapse Analytics

System Properties Comparison GBase vs. HyperSQL vs. Ignite vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

An analytical database for business intelligence with large customers in China.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Website

www.gbase.cn

hsqldb.org

ignite.apache.org

azure.microsoft.com/services/synapse-analytics

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

apacheignite.readme.io/docs

docs.microsoft.com/azure/synapse-analytics

Developer

Apache Software Foundation

Microsoft

Initial release

2001

2015

2016

Current release

GBase 8a

2.7.2, June 2023

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++, Java, .Net

C++

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X
Solaris
Windows

hosted

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC
Java

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

Java, SQL

yes (compute grid and cache interceptors can be used instead)

Transact SQL

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

yes

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