DBMS > Badger vs. GBase vs. RavenDB vs. SQream DB

System Properties Comparison Badger vs. GBase vs. RavenDB vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Open Source Operational and Transactional Enterprise NoSQL Document Database

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

github.com/dgraph-io/badger

www.gbase.cn

ravendb.net

sqream.com

Technical documentation

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

ravendb.net/docs

docs.sqream.com

Developer

DGraph Labs

General Data Technology Co., Ltd.

Hibernating Rhinos

SQream Technologies

Initial release

2017

2004

2010

2017

Current release

GBase 8a, GBase 8s, GBase 8c

5.4, July 2022

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL version 3, commercial license available

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

C, Java, Python

C++, CUDA, Haskell, Java, Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Standard with numerous extensions

SQL-like query language (RQL)

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

.Net
JDBC
ODBC

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

yes

Authorization levels configured per client per database

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