DBMS > BigObject vs. Geode vs. JanusGraph vs. Postgres-XL

System Properties Comparison BigObject vs. Geode vs. JanusGraph vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

Technical documentation

docs.bigobject.io

geode.apache.org/docs

docs.janusgraph.org

www.postgres-xl.org/documentation

Developer

BigObject, Inc.

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

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2015

2002

2017

2014

since 2012, originally named StormDB

Current release

1.1, February 2017

0.6.3, February 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Unix
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (OQL)

yes

distributed, parallel query execution

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

Supported programming languages

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

Clojure
Java
Python

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

Server-side scripts

Stored procedures

Lua

user defined functions

yes

user defined functions

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Relationships in graphs

yes

Transaction concepts

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

yes, on a single node

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights per client and object definable

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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