DBMS > Atos Standard Common Repository vs. Google BigQuery vs. LokiJS vs. Microsoft Azure Data Explorer vs. PouchDB

System Properties Comparison Atos Standard Common Repository vs. Google BigQuery vs. LokiJS vs. Microsoft Azure Data Explorer vs. PouchDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

Fully managed big data interactive analytics platform

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Key-value store

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	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

cloud.google.com/bigquery

github.com/techfort/LokiJS

azure.microsoft.com/services/data-explorer

pouchdb.com

Technical documentation

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

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

pouchdb.com/guides

Developer

Atos Convergence Creators

Google

Microsoft

Apache Software Foundation

Initial release

2016

2010

2014

2019

2012

Current release

1703

cloud service with continuous releases

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

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

Java

JavaScript

Server operating systems

Linux

hosted

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

hosted

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

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

optional

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

via views

all fields are automatically indexed

yes

via views

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

APIs and other access methods

LDAP

RESTful HTTP/JSON API

JavaScript API

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

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

Yes, possible languages: KQL, Python, R

View functions in JavaScript

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Since BigQuery is designed for querying data

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Azure Active Directory Authentication

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