DBMS > Apache Impala vs. Apache Jena - TDB vs. BigchainDB vs. MySQL vs. NCache

System Properties Comparison Apache Impala vs. Apache Jena - TDB vs. BigchainDB vs. MySQL vs. NCache

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Widely used open source RDBMS

Open-Source and Enterprise in-memory Key-Value Store

Primary database model

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store

Document store
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Website

impala.apache.org

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

www.bigchaindb.com

www.mysql.com

www.alachisoft.com/ncache

Technical documentation

impala.apache.org/impala-docs.html

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

bigchaindb.readthedocs.io/en/latest

dev.mysql.com/doc

www.alachisoft.com/resources/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

originally developed by HP Labs

Oracle

since 2010, originally MySQL AB, then Sun

Alachisoft

Initial release

2013

2000

2016

1995

2005

Current release

4.1.0, June 2022

4.9.0, July 2023

8.4.0, April 2024

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache License, Version 2.0

Open Source

AGPL v3

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

Python

C and C++

C#, .NET, .NET Core, Java

Server operating systems

Linux

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

RDF Schemas

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

JDBC
ODBC

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

Java

Go
Haskell
Java
JavaScript
Python
Ruby

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

support for stored procedures with SQL-Server CLR

Triggers

yes

via event handler

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

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

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

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 for users, groups and roles

based on Apache Sentry and Kerberos

Access control via Jena Security

yes

Users with fine-grained authorization concept

no user groups or roles

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Market metrics

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Licensing and pricing models

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