DBMS > Derby vs. Graph Engine vs. JaguarDB vs. XTDB

System Properties Comparison Derby vs. Graph Engine vs. JaguarDB vs. XTDB

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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 in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Performant, highly scalable DBMS for AI and IoT applications

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Key-value store
Vector DBMS

Document store

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

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

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

db.apache.org/derby

www.graphengine.io

www.jaguardb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.graphengine.io/docs/manual

www.jaguardb.com/support.html

www.xtdb.com/docs

Developer

Apache Software Foundation

Microsoft

DataJaguar, Inc.

Juxt Ltd.

Initial release

1997

2010

2015

2019

Current release

10.17.1.0, November 2023

3.3 July 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

MIT License

Open Source

GPL V3.0

Open Source

MIT 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

Java

.NET and C

C++

the server part. Clients available in other languages

Clojure

Server operating systems

All OS with a Java VM

.NET

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC

RESTful HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Java

C#
C++
F#
Visual Basic

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

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

rights management via user accounts

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