DBMS > Cachelot.io vs. Google BigQuery vs. JaguarDB vs. SAP IQ vs. XTDB

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

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Large scale data warehouse service with append-only tables

Performant, highly scalable DBMS for AI and IoT applications

Columnar RDBMS optimized for Big Data analytics

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

column-oriented

Document store

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

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cachelot.io

cloud.google.com/bigquery

www.jaguardb.com

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigquery/docs

www.jaguardb.com/support.html

help.sap.com/docs/SAP_IQ

www.xtdb.com/docs

Developer

Google

DataJaguar, Inc.

SAP, formerly Sybase

Juxt Ltd.

Initial release

2015

2010

2015

1994

2019

Current release

3.3 July 2023

16.1 SPS04, April 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

GPL V3.0

commercial

Open Source

MIT License

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++

the server part. Clients available in other languages

Clojure

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

Memcached protocol

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP REST
JDBC

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Clojure
Java

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

SAP/Sybase Replication Server

yes, each node contains all data

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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)

rights management via user accounts

fine grained access rights according to SQL-standard

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