DBMS > AlaSQL vs. Drizzle vs. Google Cloud Bigtable vs. Ingres vs. SpatiaLite

System Properties Comparison AlaSQL vs. Drizzle vs. Google Cloud Bigtable vs. Ingres vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

JavaScript DBMS library

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Well established RDBMS

Spatial extension of SQLite

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

alasql.org

cloud.google.com/bigtable

www.actian.com/databases/ingres

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

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigtable/docs

docs.actian.com/ingres

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

Developer

Andrey Gershun & Mathias R. Wulff

Drizzle project, originally started by Brian Aker

Google

Actian Corporation

Alessandro Furieri

Initial release

2014

2008

2015

1974

originally developed at University Berkely in early 1970s

2008

Current release

7.2.4, September 2012

11.2, May 2022

5.0.0, August 2020

License

Commercial or Open Source

Open Source

MIT-License

Open Source

GNU GPL

commercial

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
OS X

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

server-less

Data scheme

schema-free

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

with proprietary extensions

yes

APIs and other access methods

JavaScript API

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

JavaScript

C
C++
Java
PHP

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

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

Ingres Replicator

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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