DBMS > Derby vs. Drizzle vs. Microsoft Azure Synapse Analytics vs. ReductStore

System Properties Comparison Derby vs. Drizzle vs. Microsoft Azure Synapse Analytics vs. ReductStore

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS

Time Series DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

db.apache.org/derby

azure.microsoft.com/services/synapse-analytics

github.com/reductstore
www.reduct.store

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

www.reduct.store/docs

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Microsoft

ReductStore LLC

Initial release

1997

2008

2016

2023

Current release

10.17.1.0, November 2023

7.2.4, September 2012

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU GPL

commercial

Open Source

Business Source License 1.1

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++

C++, Rust

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

hosted

Docker
Linux
macOS
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

with proprietary extensions

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

Java

C
C++
Java
PHP

C#
Java
PHP

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

Triggers

yes

hooks for callbacks inside the server can be used.

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

Source-replica replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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