DBMS > Bangdb vs. GridGain vs. Interbase

System Properties Comparison Bangdb vs. GridGain vs. Interbase

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Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

Light-weight proven RDBMS

originally from Borland

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial 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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Website

bangdb.com

www.gridgain.com

www.embarcadero.com/products/interbase

Technical documentation

docs.bangdb.com

www.gridgain.com/docs/index.html

docs.embarcadero.com/products/interbase

Developer

Sachin Sinha, BangDB

GridGain Systems, Inc.

Embarcadero

Initial release

2012

2007

1984

Current release

BangDB 2.0, October 2021

GridGain 8.5.1

InterBase 2020, December 2019

License

Commercial or Open Source

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java, C++, .Net

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Android
iOS
Linux
OS X
Windows

Data scheme

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.

yes

export as XML data possible

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

Interbase procedure and trigger language

Triggers

yes, Notifications (with Streaming only)

yes (cache interceptors and events)

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes (replicated cache)

Interbase Change Views

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Multiversion concurreny control

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

yes

User concepts

Access control

yes (enterprise version only)

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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