DBMS > AlaSQL vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. HEAVY.AI vs. LevelDB vs. Microsoft Azure Cosmos DB

System Properties Comparison AlaSQL vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. HEAVY.AI vs. LevelDB vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

alasql.org

www.alibabacloud.com/product/hybriddb-postgresql

github.com/heavyai/heavydb
www.heavy.ai

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

Technical documentation

github.com/AlaSQL/alasql

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

docs.heavy.ai

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/azure/cosmos-db

Developer

Andrey Gershun & Mathias R. Wulff

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

HEAVY.AI, Inc.

Google

Microsoft

Initial release

2014

2016

2011

2014

Current release

5.10, January 2022

1.23, February 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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

JavaScript

C++ and CUDA

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Linux

Illumos
Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

SQL-like query language

APIs and other access methods

JavaScript API

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

JavaScript

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC/Thrift
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Round robin

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Multi-source replication

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

with automatic compression on writes

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 can be defined down to the item level

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