DBMS > GBase vs. Microsoft Azure AI Search vs. NSDb vs. Sphinx

System Properties Comparison GBase vs. Microsoft Azure AI Search vs. NSDb vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Secondary database models

Vector DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.gbase.cn

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

nsdb.io

sphinxsearch.com

Technical documentation

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

nsdb.io/Architecture

sphinxsearch.com/docs

Developer

General Data Technology Co., Ltd.

Microsoft

Sphinx Technologies Inc.

Initial release

2004

2015

2017

2001

Current release

GBase 8a, GBase 8s, GBase 8c

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

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

C, Java, Python

Java, Scala

C++

Server operating systems

Linux

hosted

Linux
macOS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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 fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

gRPC
HTTP REST
WebSocket

Proprietary protocol

Supported programming languages

C#
Java
JavaScript
Python

Java
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

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

Implicit feature of the cloud service

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

Foreign keys

Referential integrity

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

Using Apache Lucene

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.

User concepts

Access control

yes

using Azure authentication

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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