DBMS > Google Cloud Datastore vs. Ingres vs. Microsoft SQL Server vs. SpatiaLite vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. Ingres vs. Microsoft SQL Server vs. SpatiaLite vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Well established RDBMS

Microsofts flagship relational DBMS

Spatial extension of SQLite

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

cloud.google.com/datastore

www.actian.com/databases/ingres

www.microsoft.com/en-us/sql-server

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

yaacomo.com

Technical documentation

cloud.google.com/datastore/docs

docs.actian.com/ingres

learn.microsoft.com/en-US/sql/sql-server

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

Developer

Google

Actian Corporation

Microsoft

Alessandro Furieri

Q2WEB GmbH

Initial release

2008

1974

originally developed at University Berkely in early 1970s

1989

2008

2009

Current release

11.2, May 2022

SQL Server 2022, November 2022

5.0.0, August 2020

License

Commercial or Open Source

commercial

restricted free version is available

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

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Implementation language

C++

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

server-less

Android
Linux
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.

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

yes

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

using Google App Engine

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Ingres Replicator

yes, but depending on the SQL-Server Edition

none

Source-replica replication

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

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

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 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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