DBMS > Apache Jena - TDB vs. Couchbase vs. Greenplum vs. GridGain vs. MongoDB

System Properties Comparison Apache Jena - TDB vs. Couchbase vs. Greenplum vs. GridGain vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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.

GridGain is an in-memory computing platform, built on Apache Ignite

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

Primary database model

RDF store

Document store

Relational DBMS

Key-value store
Relational DBMS

Document store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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	3.75
Rank	#84	Overall
	#3	RDF stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

jena.apache.org/documentation/tdb/index.html

Technical documentation

jena.apache.org/documentation/tdb/index.html

docs.couchbase.com

docs.greenplum.org

www.gridgain.com/docs/index.html

www.mongodb.com/docs/manual

Developer

Apache Software Foundation

originally developed by HP Labs

Couchbase, Inc.

Pivotal Software Inc.

GridGain Systems, Inc.

MongoDB, Inc

Initial release

2000

2011

2005

2007

2009

Current release

4.9.0, July 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

7.0.0, September 2023

GridGain 8.5.1

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

commercial

Open Source

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

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C, C++, Go and Erlang

Java, C++, .Net

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

RDF Schemas

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.

Typing

predefined data types such as float or date

yes

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

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++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

ANSI-99 for query and DML statements, subset of DDL

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
Java
Perl
Python
R

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

yes (compute grid and cache interceptors can be used instead)

JavaScript

Triggers

yes

via event handler

yes

via the TAP protocol

yes

yes (cache interceptors and events)

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

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.

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

yes (replicated cache)

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

TDB Transactions

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

In-memory capabilities

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

yes

Ephemeral buckets

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access control via Jena Security

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

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