DBMS > Google Cloud Datastore vs. Microsoft SQL Server vs. SAP Advantage Database Server vs. VictoriaMetrics

System Properties Comparison Google Cloud Datastore vs. Microsoft SQL Server vs. SAP Advantage Database Server vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Microsofts flagship relational DBMS

Low-cost RDBMS with access to ISAM and FoxPro data structures

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

cloud.google.com/datastore

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

www.sap.com/products/advantage-database-server.html

victoriametrics.com

Technical documentation

cloud.google.com/datastore/docs

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

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Google

Microsoft

Sybase, SAP

VictoriaMetrics

Initial release

2008

1989

1993

2018

Current release

SQL Server 2022, November 2022

v1.91, May 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache Version 2.0

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

Linux
Windows

FreeBSD
Linux
macOS
OpenBSD

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.

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

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

using Google App Engine

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

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes, but depending on the SQL-Server Edition

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Synchronous 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

Eventual 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

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

caching of (temporary) tables can be configured

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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