DBMS > Geode vs. OrigoDB vs. Sphinx

System Properties Comparison Geode vs. OrigoDB vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Key-value store

Document store
Object oriented DBMS

Search engine

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

Score	1.99
Rank	#133	Overall
	#23	Key-value stores

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

geode.apache.org

origodb.com

sphinxsearch.com

Technical documentation

geode.apache.org/docs

origodb.com/docs

sphinxsearch.com/docs

Developer

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

Robert Friberg et al

Sphinx Technologies Inc.

Initial release

2002

2009

under the name LiveDB

2001

Current release

1.1, February 2017

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

GPL version 2, commercial licence available

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

All OS with a Java VM

the JDK (8 or later) is also required

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (OQL)

SQL-like query language (SphinxQL)

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

.NET Client API
HTTP API
LINQ

Proprietary protocol

Supported programming languages

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

.Net

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

The original contents of fields are not stored in the Sphinx index.

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

Role based authorization

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More resources

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