DBMS > Badger vs. Geode vs. Postgres-XL vs. Sphinx

System Properties Comparison Badger vs. Geode vs. Postgres-XL vs. Sphinx

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

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

Primary database model

Key-value store

Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

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

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

github.com/dgraph-io/badger

geode.apache.org

www.postgres-xl.org

sphinxsearch.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

geode.apache.org/docs

www.postgres-xl.org/documentation

sphinxsearch.com/docs

Developer

DGraph Labs

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

Sphinx Technologies Inc.

Initial release

2017

2002

2014

since 2012, originally named StormDB

2001

Current release

1.1, February 2017

10 R1, October 2018

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Mozilla public license

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

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (OQL)

yes

distributed, parallel query execution

SQL-like query language (SphinxQL)

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

Proprietary protocol

Supported programming languages

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

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

This is how much one of the most expensive gems costs at the Tucson gem show
11 February 2024, KGUN 9 Tucson News

Apache Geode Spawns 'All Sorts of In-Memory Things'
4 January 2017, The New Stack

Where Does Apache Geode Fit in CQRS Architectures?
18 December 2016, InfoQ.com

1. Introduction to Pivotal GemFire In-Memory Data Grid and Apache Geode - Scaling Data Services with Pivotal ...
15 November 2018, O'Reilly Media

Event-Driven Architectures with Apache Geode and Spring Integration
20 March 2019, InfoQ.com

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose
2 February 2024, Towards Data Science

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Perplexity AI: From Its Use To Operation, Everything You Need To Know About Googles Newest Challenger
11 January 2024, Free Press Journal

How to Build 600+ Links in One Month
4 September 2020, Search Engine Journal

Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial
22 December 2018, WQXR Radio

provided by Google News

Share this page