DBMS > HEAVY.AI vs. Newts vs. RDF4J vs. RocksDB vs. Sphinx

System Properties Comparison HEAVY.AI vs. Newts vs. RDF4J vs. RocksDB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Time Series DBMS based on Cassandra

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

github.com/heavyai/heavydb
www.heavy.ai

opennms.github.io/newts

rdf4j.org

rocksdb.org

sphinxsearch.com

Technical documentation

docs.heavy.ai

github.com/OpenNMS/newts/wiki

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

HEAVY.AI, Inc.

OpenNMS Group

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

2016

2014

2004

2013

2001

Current release

5.10, January 2022

9.2.1, May 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++ and CUDA

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC
Thrift
Vega

HTTP REST
Java API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

Java

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

based on Cassandra

none

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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.