DBMS > Alibaba Cloud Table Store vs. Bangdb vs. Microsoft Azure Data Explorer vs. Oracle Rdb

System Properties Comparison Alibaba Cloud Table Store vs. Bangdb vs. Microsoft Azure Data Explorer vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Converged and high performance database for device data, events, time series, document and graph

Fully managed big data interactive analytics platform

Primary database model

Wide column store

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

column oriented

Relational DBMS

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	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

www.alibabacloud.com/product/table-store

bangdb.com

azure.microsoft.com/services/data-explorer

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.bangdb.com

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Alibaba

Sachin Sinha, BangDB

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2016

2012

2019

1984

Current release

BangDB 2.0, October 2021

cloud service with continuous releases

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

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, C++

Server operating systems

hosted

Linux

hosted

HP Open VMS

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

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

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

yes

secondary, composite, nested, reverse, geospatial

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

HTTP API

Proprietary protocol
RESTful HTTP API

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

Supported programming languages

Java
Python

C
C#
C++
Java
Python

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

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes, Notifications (with Streaming only)

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

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor, Knob for CAP (enterprise version only)

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

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

Access rights based on subaccounts and tokens

yes (enterprise version only)

Azure Active Directory Authentication

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