DBMS > Amazon Redshift vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx vs. Valentina Server

System Properties Comparison Amazon Redshift vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A fast-speed and highly-scalable Graph DBMS

Search-as-a-service for web and mobile app development

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

Object-relational database and reports server

Primary database model

Secondary database models

Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

aws.amazon.com/redshift

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/en-us/services/search

sphinxsearch.com

www.valentina-db.net

Technical documentation

docs.aws.amazon.com/redshift

hugegraph.apache.org/docs

learn.microsoft.com/en-us/azure/search

sphinxsearch.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Amazon (based on PostgreSQL)

Baidu

Microsoft

Sphinx Technologies Inc.

Paradigma Software

Initial release

2012

2018

2015

2001

1999

Current release

0.9

3.5.1, February 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2, commercial licence available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Unix

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
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

restricted

yes

also supports composite index and range index

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (SphinxQL)

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API

Proprietary protocol

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Groovy
Java
Python

C#
Java
JavaScript
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in Python

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

Implicit feature of the cloud service

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

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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.

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

fine grained access rights according to SQL-standard

Users, roles and permissions

yes

using Azure authentication

fine grained access rights according to SQL-standard

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