DBMS > Google BigQuery vs. H2GIS vs. Hazelcast vs. JaguarDB

System Properties Comparison Google BigQuery vs. H2GIS vs. Hazelcast vs. JaguarDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Spatial extension of H2

A widely adopted in-memory data grid

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Relational DBMS

Spatial DBMS

Key-value store

Key-value store
Vector DBMS

Secondary database models

Relational DBMS

Document store

JSON support with IMDG 3.12

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
	#7	Spatial DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

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

Website

cloud.google.com/bigquery

www.h2gis.org

hazelcast.com

www.jaguardb.com

Technical documentation

cloud.google.com/bigquery/docs

www.h2gis.org/docs/home

hazelcast.org/imdg/docs

www.jaguardb.com/support.html

Developer

Google

CNRS

Hazelcast

DataJaguar, Inc.

Initial release

2010

2013

2008

2015

Current release

5.3.6, November 2023

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL V3.0

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

C++

the server part. Clients available in other languages

Server operating systems

hosted

All OS with a Java VM

Linux

Data scheme

yes

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

based on H2

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

Replicated Map

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual 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

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

based on H2

Role-based access control

rights management via user accounts

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