DBMS > Coveo vs. Databend vs. Microsoft SQL Server vs. Sphinx vs. STSdb

System Properties Comparison Coveo vs. Databend vs. Microsoft SQL Server vs. Sphinx vs. STSdb

Editorial information provided by DB-Engines

Name

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Microsofts flagship relational DBMS

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.coveo.com

github.com/datafuselabs/databend
www.databend.com

www.microsoft.com/en-us/sql-server

sphinxsearch.com

github.com/STSSoft/STSdb4

Technical documentation

docs.coveo.com

docs.databend.com

learn.microsoft.com/en-US/sql/sql-server

sphinxsearch.com/docs

Developer

Coveo

Databend Labs

Microsoft

Sphinx Technologies Inc.

STS Soft SC

Initial release

2012

2021

1989

2001

2011

Current release

1.0.59, April 2023

SQL Server 2022, November 2022

3.5.1, February 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

C++

Server operating systems

hosted

hosted
Linux
macOS

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Windows

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Proprietary protocol

.NET Client API

Supported programming languages

C#
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

granular access controls, API key management, content filters

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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