DBMS > AlaSQL vs. AntDB vs. JSqlDb vs. Microsoft Azure Data Explorer

System Properties Comparison AlaSQL vs. AntDB vs. JSqlDb vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

JavaScript DBMS library

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

JavaScript Query Language Database, stores JavaScript objects and primitives

Fully managed big data interactive analytics platform

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

column oriented

Secondary database models

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

Score	0.23
Rank	#317	Overall
	#141	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Website

alasql.org

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

jsqldb.org (offline)

azure.microsoft.com/services/data-explorer

Technical documentation

github.com/AlaSQL/alasql

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

Developer

Andrey Gershun & Mathias R. Wulff

AsiaInfo Technologies Limited

Konrad von Backstrom

Microsoft

Initial release

2014

2018

2019

Current release

0.8, December 2018

cloud service with continuous releases

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

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

Server operating systems

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

Linux
macOS
Windows

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

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 fields are automatically indexed

SQL

Support of SQL

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

SQL2016 compliant

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JavaScript API

JDBC
MySQL protocol compliant
ODBC

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

Supported programming languages

JavaScript

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

Server-side scripts

Stored procedures

functions in JavaScript

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

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. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

using RocksDB

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

Azure Active Directory Authentication

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More resources

DB-Engines blog posts

AntDB: Answer to Database Evolution - Hyperconverged All-in-One Streaming Engine
22 June 2023, Bei Mo, AntDB (sponsor)

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