DBMS > GBase vs. Microsoft Azure Data Explorer vs. OrigoDB vs. searchxml

System Properties Comparison GBase vs. Microsoft Azure Data Explorer vs. OrigoDB vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Fully managed big data interactive analytics platform

A fully ACID in-memory object graph database

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

column oriented

Document store
Object oriented DBMS

Native XML DBMS
Search engine

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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

www.gbase.cn

azure.microsoft.com/services/data-explorer

origodb.com

www.searchxml.net/category/products

Technical documentation

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

origodb.com/docs

www.searchxml.net/support/handouts

Developer

General Data Technology Co., Ltd.

Microsoft

Robert Friberg et al

informationpartners gmbh

Initial release

2004

2019

2009

under the name LiveDB

2015

Current release

GBase 8a, GBase 8s, GBase 8c

cloud service with continuous releases

1.0

License

Commercial or Open Source

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

C, Java, Python

C++

Server operating systems

Linux

hosted

Linux
Windows

Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

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

User defined using .NET types and collections

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

can be achieved using .NET

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Standard with numerous extensions

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

.NET Client API
HTTP API
LINQ

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

.Net

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

yes

on the application server

Triggers

yes

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

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

yes

sychronisation to multiple collections

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Azure Active Directory Authentication

Role based authorization

Domain, group and role-based access control at the document level and for application services

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