DBMS > Bangdb vs. GeoSpock vs. RavenDB vs. SWC-DB vs. Transbase

System Properties Comparison Bangdb vs. GeoSpock vs. RavenDB vs. SWC-DB vs. Transbase

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

Spatial and temporal data processing engine for extreme data scale

Open Source Operational and Transactional Enterprise NoSQL Document Database

A high performance, scalable Wide Column DBMS

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

Time Series DBMS

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

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	3.01
Rank	#101	Overall
	#17	Document stores

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

bangdb.com

geospock.com

ravendb.net

github.com/kashirin-alex/swc-db
www.swcdb.org

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

Technical documentation

docs.bangdb.com

ravendb.net/docs

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

Developer

Sachin Sinha, BangDB

GeoSpock

Hibernating Rhinos

Alex Kashirin

Transaction Software GmbH

Initial release

2012

2010

2020

1987

Current release

BangDB 2.0, October 2021

2.0, September 2019

5.4, July 2022

0.5, April 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

AGPL version 3, commercial license available

Open Source

GPL V3

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java, Javascript

C++

C and C++

Server operating systems

Linux

hosted

Linux
macOS
Raspberry Pi
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

temporal, categorical

yes

SQL

Support of SQL

SQL like support with command line tool

ANSI SQL for query only (using Presto)

SQL-like query language (RQL)

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

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

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

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

C++

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

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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

yes

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Access rights for users can be defined per table

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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