DBMS > Apache Jena - TDB vs. Elasticsearch vs. Google Cloud Spanner vs. MongoDB vs. searchxml

System Properties Comparison Apache Jena - TDB vs. Elasticsearch vs. Google Cloud Spanner vs. MongoDB vs. searchxml

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, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

Primary database model

Native XML DBMS
Search engine

Secondary database models

Document store
Spatial DBMS
Vector 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	3.62
Rank	#83	Overall
	#3	RDF stores

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

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

www.elastic.co/elasticsearch

cloud.google.com/spanner

www.mongodb.com

www.searchxml.net/category/products

Technical documentation

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

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

cloud.google.com/spanner/docs

www.mongodb.com/docs/manual

www.searchxml.net/support/handouts

Developer

Apache Software Foundation

originally developed by HP Labs

Elastic

Google

MongoDB, Inc

informationpartners gmbh

Initial release

2000

2010

2017

2009

2015

Current release

4.9.0, July 2023

8.6, January 2023

6.0.7, June 2023

1.0

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Elastic License

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.

commercial

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

RDF Schemas

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

Query statements complying to ANSI 2011

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

Java API
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

JavaScript

yes

on the application server

Triggers

yes

via event handler

yes

by using the 'percolation' feature

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

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

none

yes

Multi-source replication with 3 replicas for regional instances.

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

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

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

Strict serializable isolation

Multi-document ACID Transactions with snapshot isolation

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

Memcached and Redis integration

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access control via Jena Security

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

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

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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