DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Blueflood vs. Databend vs. Hazelcast vs. Microsoft SQL Server

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Blueflood vs. Databend vs. Hazelcast vs. Microsoft SQL Server

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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A widely adopted in-memory data grid

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
Spatial DBMS

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	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

blueflood.io

github.com/datafuselabs/databend
www.databend.com

hazelcast.com

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

Technical documentation

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

github.com/rax-maas/blueflood/wiki

docs.databend.com

hazelcast.org/imdg/docs

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

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Rackspace

Databend Labs

Hazelcast

Microsoft

Initial release

2016

2013

2021

2008

1989

Current release

1.0.59, April 2023

5.3.6, November 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

Rust

Java

C++

Server operating systems

hosted

Linux
OS X

hosted
Linux
macOS

All OS with a Java VM

Linux
Windows

Data scheme

yes

predefined scheme

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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

CLI Client
JDBC
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

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

Supported programming languages

C
Java
Perl
Python
R

Go
Java
JavaScript (Node.js)
Python
Rust

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

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

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

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

none

yes

Replicated Map

yes, but depending on the SQL-Server Edition

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

one or two-phase-commit; repeatable reads; read commited

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

Users with fine-grained authorization concept, user roles

Role-based access control

fine grained access rights according to SQL-standard

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