DBMS > Derby vs. Kyligence Enterprise vs. Microsoft Azure Synapse Analytics vs. TimesTen

System Properties Comparison Derby vs. Kyligence Enterprise vs. Microsoft Azure Synapse Analytics vs. TimesTen

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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.

A distributed analytics engine for big data, built on top of Apache Kylin

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

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

db.apache.org/derby

kyligence.io/kyligence-enterprise

azure.microsoft.com/services/synapse-analytics

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

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Kyligence, Inc.

Microsoft

Oracle, TimesTen Performance Software, HP

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

Initial release

1997

2016

1998

Current release

10.17.1.0, November 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache version 2

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++

Server operating systems

All OS with a Java VM

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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 SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

C#
Java
PHP

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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