DBMS > AntDB vs. Hypertable vs. Microsoft Azure Data Explorer

System Properties Comparison AntDB vs. Hypertable vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Fully managed big data interactive analytics platform

Primary database model

Relational DBMS

Wide column store

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	0.23
Rank	#317	Overall
	#141	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Website

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

azure.microsoft.com/services/data-explorer

Technical documentation

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

Developer

AsiaInfo Technologies Limited

Hypertable Inc.

Microsoft

Initial release

2009

2019

Current release

0.9.8.11, March 2016

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license 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

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Data scheme

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

restricted

only exact value or prefix value scans

all fields are automatically indexed

SQL

Support of SQL

SQL2016 compliant

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC
MySQL protocol compliant
ODBC

C++ API
Thrift

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

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

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

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

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

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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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Recent citations in the news

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

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16 August 2022, Gigaom

provided by Google News

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