DBMS > Databend vs. Ehcache vs. JaguarDB vs. Transbase

System Properties Comparison Databend vs. Ehcache vs. JaguarDB 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

A widely adopted Java cache with tiered storage options

Performant, highly scalable DBMS for AI and IoT applications

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

Primary database model

Relational DBMS

Key-value store

Key-value store
Vector DBMS

Relational DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

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

www.ehcache.org

www.jaguardb.com

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

Technical documentation

docs.databend.com

www.ehcache.org/documentation

www.jaguardb.com/support.html

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

Developer

Databend Labs

Terracotta Inc, owned by Software AG

DataJaguar, Inc.

Transaction Software GmbH

Initial release

2021

2009

2015

1987

Current release

1.0.59, April 2023

3.10.0, March 2022

3.3 July 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL V3.0

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

Java

C++

the server part. Clients available in other languages

C and C++

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JCache

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Java

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

Multi-source replication

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

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

rights management via user accounts

fine grained access rights according to SQL-standard

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