DBMS > BigObject vs. Geode vs. Netezza vs. RocksDB

System Properties Comparison BigObject vs. Geode vs. Netezza vs. RocksDB

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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

Data warehouse and analytics appliance part of IBM PureSystems

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Key-value store

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	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

bigobject.io

geode.apache.org

www.ibm.com/products/netezza

rocksdb.org

Technical documentation

docs.bigobject.io

geode.apache.org/docs

github.com/facebook/rocksdb/wiki

Developer

BigObject, Inc.

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

IBM

Facebook, Inc.

Initial release

2015

2002

2000

2013

Current release

1.1, February 2017

8.11.4, April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

BSD

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

C++

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

included in appliance

Linux

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (OQL)

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
OLE DB

C++ API
Java API

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Lua

user defined functions

yes

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

yes, on a single node

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

Users with fine-grained authorization concept

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