DBMS > Google BigQuery vs. JaguarDB vs. SAP IQ vs. Snowflake vs. XTDB

System Properties Comparison Google BigQuery vs. JaguarDB vs. SAP IQ vs. Snowflake vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

column-oriented

Relational DBMS

Document store

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

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	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cloud.google.com/bigquery

www.jaguardb.com

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

www.snowflake.com

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

docs.snowflake.net/manuals/index.html

www.xtdb.com/docs

Developer

Google

DataJaguar, Inc.

SAP, formerly Sybase

Snowflake Computing Inc.

Juxt Ltd.

Initial release

2010

2015

1994

2014

2019

Current release

3.3 July 2023

16.1 SPS04, April 2019

1.19, September 2021

License

Commercial or Open Source

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

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Implementation language

C++

the server part. Clients available in other languages

Clojure

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

hosted

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

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

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

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.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

JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

SAP/Sybase Replication Server

yes

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

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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