DBMS > Databend vs. Derby vs. Microsoft Azure Synapse Analytics vs. Transbase

System Properties Comparison Databend vs. Derby vs. Microsoft Azure Synapse Analytics vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

db.apache.org/derby

azure.microsoft.com/services/synapse-analytics

www.transaction.de/en/products/transbase.html

Technical documentation

docs.databend.com

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

docs.microsoft.com/azure/synapse-analytics

www.transaction.de/en/products/transbase/features.html

Developer

Databend Labs

Apache Software Foundation

Microsoft

Transaction Software GmbH

Initial release

2021

1997

2016

1987

Current release

1.0.59, April 2023

10.17.1.0, November 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

commercial

free development license

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

Rust

Java

C++

C and C++

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

hosted

FreeBSD
Linux
macOS
Solaris
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

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Java

C#
Java
PHP

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Source-replica replication

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

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

yes

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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