DBMS > Atos Standard Common Repository vs. GridDB vs. IRONdb vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. GridDB vs. IRONdb vs. Microsoft Azure Data Explorer

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Fully managed big data interactive analytics platform

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

column oriented

Secondary database models

Key-value store
Relational 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	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Website

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

griddb.net

www.circonus.com/solutions/time-series-database/

azure.microsoft.com/services/data-explorer

Technical documentation

docs.griddb.net

docs.circonus.com/irondb/category/getting-started

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

Developer

Atos Convergence Creators

Toshiba Corporation

Circonus LLC.

Microsoft

Initial release

2016

2013

2017

2019

Current release

1703

5.1, August 2022

V0.10.20, January 2018

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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

Java

C++

C and C++

Server operating systems

Linux

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

optional

yes

numerical, string, blob, geometry, boolean, timestamp

yes

text, numeric, histograms

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

all fields are automatically indexed

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language (Circonus Analytics Query Language: CAQL)

Kusto Query Language (KQL), SQL subset

APIs and other access methods

LDAP

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API

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

Supported programming languages

All languages with LDAP bindings

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Server-side scripts

Stored procedures

yes, in Lua

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

cell division

Sharding

Automatic, metric affinity per node

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

configurable replication factor, datacenter aware

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

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency within container, eventual consistency across containers

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID at container level

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

LDAP bind authentication

Access rights for users can be defined per database

Azure Active Directory Authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

TOSHIBA DIGITAL SOLUTIONS CORPORATION
1 November 2020, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data Management
3 December 2019, global.toshiba

Amazon Proposes to Develop New Data Center Campus in Virginia
26 August 2022, w.media

’s SQL Interface, Aims to Accelerate Open Innovation
17 June 2020, global.toshiba

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer
31 May 2024, azure.microsoft.com

Update records in a Kusto Database (public preview)
20 February 2024, azure.microsoft.com

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints
5 February 2024, azure.microsoft.com

Announcing General Availability of Graph Semantics in Kusto
27 May 2024, azure.microsoft.com

Migration of Azure Virtual Network injected Azure Data Explorer cluster to Private Endpoints
4 December 2023, azure.microsoft.com

provided by Google News

Share this page