DBMS > AlaSQL vs. Cassandra vs. Google Cloud Datastore vs. Microsoft Azure AI Search

System Properties Comparison AlaSQL vs. Cassandra vs. Google Cloud Datastore vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

Search-as-a-service for web and mobile app development

Primary database model

Document store
Relational DBMS

Wide column store

Document store

Search engine

Secondary database models

Vector DBMS

starting with release V5

Vector DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Website

alasql.org

cassandra.apache.org

cloud.google.com/datastore

azure.microsoft.com/en-us/services/search

Technical documentation

github.com/AlaSQL/alasql

cassandra.apache.org/doc/latest

cloud.google.com/datastore/docs

learn.microsoft.com/en-us/azure/search

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Microsoft

Initial release

2014

2008

2015

Current release

4.1.3, July 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache version 2

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

JavaScript

Java

Server operating systems

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

BSD
Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

SQL-like SELECT, DML and DDL statements (CQL)

SQL-like query language (GQL)

APIs and other access methods

JavaScript API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

JavaScript

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication using Paxos

yes

Implicit feature of the cloud service

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

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomicity and isolation are supported for single operations

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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 can be defined per object

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

yes

using Azure authentication

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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