DBMS > Badger vs. Graph Engine vs. Oracle NoSQL vs. ToroDB vs. Valentina Server

System Properties Comparison Badger vs. Graph Engine vs. Oracle NoSQL vs. ToroDB vs. Valentina Server

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Object-relational database and reports server

Primary database model

Key-value store

Graph DBMS
Key-value store

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

github.com/dgraph-io/badger

www.graphengine.io

www.oracle.com/database/nosql/technologies/nosql

github.com/torodb/server

www.valentina-db.net

Technical documentation

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

www.graphengine.io/docs/manual

docs.oracle.com/en/database/other-databases/nosql-database/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

DGraph Labs

Microsoft

Oracle

8Kdata

Paradigma Software

Initial release

2017

2010

2011

2016

1999

Current release

23.3, December 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

AGPL-V3

commercial

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

.NET and C

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

.NET

Linux
Solaris SPARC/x86

All OS with a Java 7 VM

Linux
OS X
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

string, integer, double, boolean, date, object_id

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

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP API

ODBC

Supported programming languages

C#
C++
F#
Visual Basic

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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