DBMS > Badger vs. Dgraph vs. GridDB vs. H2 vs. SQLite

System Properties Comparison Badger vs. Dgraph vs. GridDB vs. H2 vs. SQLite

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Distributed and scalable native Graph DBMS

Scalable in-memory time series database optimized for IoT and Big Data

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

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/dgraph-io/badger

Technical documentation

godoc.org/github.com/dgraph-io/badger

dgraph.io/docs

docs.griddb.net

www.h2database.com/html/main.html

www.sqlite.org/docs.html

Developer

DGraph Labs

Dgraph Labs, Inc.

Toshiba Corporation

Thomas Mueller

Dwayne Richard Hipp

Initial release

2017

2016

2013

2005

2000

Current release

5.1, August 2022

2.2.220, July 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

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

Open Source

Public Domain

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

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux

All OS with a Java VM

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

not rigid because of 'dynamic typing' concept.

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-92 is not fully supported

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

Source-replica replication

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.