DBMS > Coveo vs. GeoSpock vs. IBM Db2 vs. InfluxDB vs. Microsoft SQL Server

System Properties Comparison Coveo vs. GeoSpock vs. IBM Db2 vs. InfluxDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

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

DBMS for storing time series, events and metrics

Microsofts flagship relational DBMS

Primary database model

Search engine

Relational DBMS

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

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
RDF store

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

with Db2 Spatial Extender

Spatial DBMS

with GEO package

Document store
Graph DBMS
Spatial DBMS

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

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.coveo.com

geospock.com

www.ibm.com/products/db2

www.influxdata.com/products/influxdb-overview

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

Technical documentation

docs.coveo.com

www.ibm.com/docs/en/db2

docs.influxdata.com/influxdb

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

Developer

Coveo

GeoSpock

IBM

Microsoft

Initial release

2012

1983

host version

2013

1989

Current release

2.0, September 2019

12.1, October 2016

2.7.6, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free version is available

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is 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

Java, Javascript

C and C++

C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X

through Homebrew

Linux
Windows

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

JDBC

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API
JSON over UDP

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

Supported programming languages

C#
Java
JavaScript
Python

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Server-side scripts

Stored procedures

yes

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

Automatic sharding

Sharding

only with Windows/Unix/Linux Version

Sharding

in enterprise version only

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

selectable replication factor

in enterprise version only

yes, but depending on the SQL-Server Edition

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

User concepts

Access control

granular access controls, API key management, content filters

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

simple rights management via user accounts

fine grained access rights according to SQL-standard

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