DBMS > Dgraph vs. H2 vs. Transbase vs. Warp 10

System Properties Comparison Dgraph vs. H2 vs. Transbase vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Graph DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

dgraph.io

www.h2database.com

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

www.warp10.io

Technical documentation

dgraph.io/docs

www.h2database.com/html/main.html

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

www.warp10.io/content/02_Getting_started

Developer

Dgraph Labs, Inc.

Thomas Mueller

Transaction Software GmbH

SenX

Initial release

2016

2005

1987

2015

Current release

2.2.220, July 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free development license

Open Source

Apache License 2.0

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

C and C++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Jupyter
WebSocket

Supported programming languages

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

Java

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Planned for future releases

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

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10 September 2020, TechCrunch

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