DBMS > Cachelot.io vs. Google BigQuery vs. IBM Db2 vs. JaguarDB vs. SAP IQ

System Properties Comparison Cachelot.io vs. Google BigQuery vs. IBM Db2 vs. JaguarDB vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Large scale data warehouse service with append-only tables

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

Performant, highly scalable DBMS for AI and IoT applications

Columnar RDBMS optimized for Big Data analytics

Primary database model

Key-value store

Relational DBMS

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

Key-value store
Vector DBMS

Relational DBMS

column-oriented

Secondary database models

Document store
RDF store

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

with Db2 Spatial Extender

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

cachelot.io

cloud.google.com/bigquery

www.ibm.com/products/db2

www.jaguardb.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2

www.jaguardb.com/support.html

help.sap.com/docs/SAP_IQ

Developer

Google

IBM

DataJaguar, Inc.

SAP, formerly Sybase

Initial release

2015

2010

1983

host version

2015

1994

Current release

12.1, October 2016

3.3 July 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

free version is available

Open Source

GPL V3.0

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

C++

C and C++

C++

the server part. Clients available in other languages

Server operating systems

FreeBSD
Linux
OS X

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

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

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Memcached protocol

RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

with separate tools (MQ, InfoSphere)

Multi-source replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

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.

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

rights management via user accounts

fine grained access rights according to SQL-standard

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