DBMS > Derby vs. HyperSQL vs. Microsoft Azure Synapse Analytics vs. Warp 10

System Properties Comparison Derby vs. HyperSQL vs. Microsoft Azure Synapse Analytics vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Time Series DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

db.apache.org/derby

hsqldb.org

azure.microsoft.com/services/synapse-analytics

www.warp10.io

Technical documentation

db.apache.org/derby/manuals/index.html

hsqldb.org/web/hsqlDocsFrame.html

docs.microsoft.com/azure/synapse-analytics

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Microsoft

SenX

Initial release

1997

2001

2016

2015

Current release

10.17.1.0, November 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

based on BSD license

commercial

Open Source

Apache License 2.0

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

Server operating systems

All OS with a Java VM

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

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

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

APIs and other access methods

JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

Java

All languages supporting JDBC/ODBC
Java

C#
Java
PHP

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

Transact SQL

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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