DBMS > Coveo vs. IBM Db2 vs. Microsoft SQL Server vs. Splice Machine

System Properties Comparison Coveo vs. IBM Db2 vs. Microsoft SQL Server vs. Splice Machine

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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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Microsofts flagship relational DBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Search engine

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

Score	2.34
Rank	#117	Overall
	#11	Search engines

Score	127.49
Rank	#8	Overall
	#5	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

www.coveo.com

www.ibm.com/products/db2

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

splicemachine.com

Technical documentation

docs.coveo.com

www.ibm.com/docs/en/db2

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

splicemachine.com/how-it-works

Developer

Coveo

IBM

Microsoft

Splice Machine

Initial release

2012

1983

host version

1989

2014

Current release

12.1, October 2016

SQL Server 2022, November 2022

3.1, March 2021

License

Commercial or Open Source

commercial

free version is available

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license 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 and C++

C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

Linux
OS X
Solaris
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

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C#
Java
JavaScript
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

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

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

only with Windows/Unix/Linux Version

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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