DBMS > Geode vs. Greenplum vs. MongoDB vs. searchxml vs. TimesTen

System Properties Comparison Geode vs. Greenplum vs. MongoDB vs. searchxml vs. TimesTen

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

DBMS for structured and unstructured content wrapped with an application server

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store

Relational DBMS

Document store

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

geode.apache.org

greenplum.org

www.mongodb.com

www.searchxml.net/category/products

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

geode.apache.org/docs

docs.greenplum.org

www.mongodb.com/docs/manual

www.searchxml.net/support/handouts

docs.oracle.com/database/timesten-18.1

Developer

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

Pivotal Software Inc.

MongoDB, Inc

informationpartners gmbh

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2002

2005

2009

2015

1998

Current release

1.1, February 2017

7.0.0, September 2023

6.0.7, June 2023

1.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

Java

C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Linux
OS X
Solaris
Windows

Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

C
Java
Perl
Python
R

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

C++

most other programming languages supported via APIs

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

JavaScript

yes

on the application server

PL/SQL

Triggers

yes

Cache Event Listeners

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

sychronisation to multiple collections

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

yes, on a single node

ACID

Multi-document ACID Transactions with snapshot isolation

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights per client and object definable

fine grained access rights according to SQL-standard

Access rights for users and roles

Domain, group and role-based access control at the document level and for application services

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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.