DBMS > Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. SpatiaLite vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. SpatiaLite vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Spatial extension of SQLite

Object-relational database and reports server

Primary database model

Secondary database models

Relational DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

cloud.google.com/datastore

azure.microsoft.com/services/synapse-analytics

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

www.valentina-db.net

Technical documentation

cloud.google.com/datastore/docs

docs.microsoft.com/azure/synapse-analytics

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Google

Microsoft

Alessandro Furieri

Paradigma Software

Initial release

2008

2016

2008

1999

Current release

5.0.0, August 2020

5.7.5

License

Commercial or Open Source

commercial

Open Source

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

commercial

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++

Server operating systems

hosted

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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

SQL-like query language (GQL)

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ODBC

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
Java
PHP

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

using Google App Engine

Transact SQL

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

yes

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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