DBMS > Apache Jena - TDB vs. Elasticsearch vs. etcd vs. HugeGraph vs. MySQL

System Properties Comparison Apache Jena - TDB vs. Elasticsearch vs. etcd vs. HugeGraph vs. MySQL

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 distributed reliable key-value store

A fast-speed and highly-scalable Graph DBMS

Widely used open source RDBMS

Primary database model

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

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

www.elastic.co/elasticsearch

etcd.io
github.com/etcd-io/etcd

github.com/hugegraph
hugegraph.apache.org

www.mysql.com

Technical documentation

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

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

hugegraph.apache.org/docs

dev.mysql.com/doc

Developer

Apache Software Foundation

originally developed by HP Labs

Elastic

Baidu

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2000

2010

2018

1995

Current release

4.9.0, July 2023

8.6, January 2023

3.4, August 2019

0.9

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Elastic License

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
Windows

experimental

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

RDF Schemas

schema-free

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

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

Secondary indexes

yes

All search fields are automatically indexed

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

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
JSON over HTTP

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Groovy
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes

proprietary syntax

Triggers

yes

via event handler

yes

by using the 'percolation' feature

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

via hugegraph-spark

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

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

TDB Transactions

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

User concepts

Access control

Access control via Jena Security

Users, roles and permissions

Users with fine-grained authorization concept

no user groups or roles

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