DBMS > Google BigQuery vs. HEAVY.AI vs. SiriDB vs. SpatiaLite

System Properties Comparison Google BigQuery vs. HEAVY.AI vs. SiriDB vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Open Source Time Series DBMS

Spatial extension of SQLite

Primary database model

Relational DBMS

Time Series DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.56
Rank	#142	Overall
	#3	Spatial DBMS

Website

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

siridb.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

cloud.google.com/bigquery/docs

docs.heavy.ai

docs.siridb.com

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Google

HEAVY.AI, Inc.

Cesbit

Alessandro Furieri

Initial release

2010

2016

2017

2008

Current release

5.10, January 2022

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

MIT License

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++ and CUDA

C++

Server operating systems

hosted

Linux

server-less

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

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

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.

yes

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

simple rights management via user accounts

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