DBMS > AlaSQL vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. Transwarp KunDB

System Properties Comparison AlaSQL vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Fully managed big data interactive analytics platform

NewSQL database with distributed OLTP and SQL

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Document store
Relational DBMS

Relational DBMS

column oriented

Document store
Relational DBMS

Relational DBMS

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	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Website

alasql.org

azure.microsoft.com/services/data-explorer

www.sequoiadb.com

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/AlaSQL/alasql

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

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Andrey Gershun & Mathias R. Wulff

Microsoft

Sequoiadb Ltd.

Transwarp

Initial release

2014

2019

2013

Current release

cloud service with continuous releases

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

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

hosted

Linux

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

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

yes

oid, date, timestamp, binary, regex

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

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

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

Kusto Query Language (KQL), SQL subset

SQL-like query language

yes

APIs and other access methods

JavaScript API

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

proprietary protocol using JSON

Supported programming languages

JavaScript

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

JavaScript

yes

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

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.

Source-replica replication

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

Eventual Consistency
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

Document is locked during a transaction

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

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

simple password-based access control

yes

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