DBMS > Bangdb vs. Geode vs. InfinityDB vs. Postgres-XL

System Properties Comparison Bangdb vs. Geode vs. InfinityDB vs. Postgres-XL

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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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A Java embedded Key-Value Store which extends the Java Map interface

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

Technical documentation

docs.bangdb.com

geode.apache.org/docs

boilerbay.com/infinitydb/manual

www.postgres-xl.org/documentation

Developer

Sachin Sinha, BangDB

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Boiler Bay Inc.

Initial release

2012

2002

2014

since 2012, originally named StormDB

Current release

BangDB 2.0, October 2021

1.1, February 2017

4.0

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Mozilla public license

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, C++

Java

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

All OS with a Java VM

Linux
macOS

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

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

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

XML type, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (OQL)

yes

distributed, parallel query execution

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Java
Python

.Net
All JVM based languages
C++
Groovy
Java
Scala

Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

Cache Event Listeners

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source 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

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

MVCC

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

yes

User concepts

Access control

yes (enterprise version only)

Access rights per client and object definable

fine grained access rights according to SQL-standard

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