DBMS > HugeGraph vs. Machbase Neo vs. SAP IQ vs. Sphinx

System Properties Comparison HugeGraph vs. Machbase Neo vs. SAP IQ vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

TimeSeries DBMS for AIoT and BigData

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

column-oriented

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

github.com/hugegraph
hugegraph.apache.org

machbase.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

sphinxsearch.com

Technical documentation

hugegraph.apache.org/docs

machbase.com/dbms

help.sap.com/docs/SAP_IQ

sphinxsearch.com/docs

Developer

Baidu

Machbase

SAP, formerly Sybase

Sphinx Technologies Inc.

Initial release

2018

2013

1994

2001

Current release

0.9

V8.0, August 2023

16.1 SPS04, April 2019

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

commercial

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

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Implementation language

Java

C++

Server operating systems

Linux
macOS
Unix

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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

also supports composite index and range index

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Proprietary protocol

Supported programming languages

Groovy
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

SAP/Sybase Replication Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

volatile and lookup table

User concepts

Access control

Users, roles and permissions

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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