DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Blueflood vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. Rockset

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Blueflood vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. Rockset

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Scalable TimeSeries DBMS based on Cassandra

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

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Time Series DBMS

Key-value store
Wide column store

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

blueflood.io

cloud.google.com/bigtable

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

rockset.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

github.com/rax-maas/blueflood/wiki

cloud.google.com/bigtable/docs

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

docs.rockset.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Rackspace

Google

Microsoft

Rockset

Initial release

2016

2013

2015

1989

2019

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

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

Java

C++

Server operating systems

hosted

Linux
OS X

hosted

Linux
Windows

hosted

Data scheme

yes

predefined scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

HTTP REST

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

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

HTTP REST

Supported programming languages

C
Java
Perl
Python
R

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

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

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

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

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

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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