DBMS > AlaSQL vs. Firebase Realtime Database vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer

System Properties Comparison AlaSQL vs. Firebase Realtime Database vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

Globally distributed, horizontally scalable, multi-model database service

Fully managed big data interactive analytics platform

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

column oriented

Secondary database models

Spatial DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Website

alasql.org

firebase.google.com/products/realtime-database

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

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/data-explorer

Technical documentation

github.com/AlaSQL/alasql

firebase.google.com/docs/database

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/data-explorer

Developer

Andrey Gershun & Mathias R. Wulff

Google

acquired by Google 2014

HEAVY.AI, Inc.

Microsoft

Initial release

2014

2012

2016

2014

2019

Current release

5.10, January 2022

cloud service with continuous releases

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2; enterprise edition available

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

Server operating systems

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

hosted

Linux

hosted

Data scheme

schema-free

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

JSON types

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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

all fields are automatically indexed

SQL

Support of SQL

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

yes

SQL-like query language

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JavaScript API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

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

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

JavaScript

Java
JavaScript
Objective-C

All languages supporting JDBC/ODBC/Thrift
Python

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

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

limited functionality with using 'rules'

JavaScript

Yes, possible languages: KQL, Python, R

Triggers

yes

Callbacks are triggered when data changes

JavaScript

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate 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

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Azure Active Directory Authentication

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