DBMS > Bangdb vs. GeoSpock vs. Spark SQL vs. Transbase vs. Yanza

System Properties Comparison Bangdb vs. GeoSpock vs. Spark SQL vs. Transbase vs. Yanza

Editorial information provided by DB-Engines

Name

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

Yanza seems to be discontinued. Therefore it is 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

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Time Series DBMS for IoT Applications

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

bangdb.com

geospock.com

spark.apache.org/sql

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

yanza.com

Technical documentation

docs.bangdb.com

spark.apache.org/docs/latest/sql-programming-guide.html

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

Developer

Sachin Sinha, BangDB

GeoSpock

Apache Software Foundation

Transaction Software GmbH

Yanza

Initial release

2012

2014

1987

2015

Current release

BangDB 2.0, October 2021

2.0, September 2019

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

commercial

free development license

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

Java, Javascript

Scala

C and C++

Server operating systems

Linux

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Windows

Data scheme

schema-free

yes

schema-free

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 DML and DDL statements

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Supported programming languages

C
C#
C++
Java
Python

Java
Python
R
Scala

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Timer and event based

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

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

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, 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

fine grained access rights according to SQL-standard

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