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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. InfluxDB vs. JanusGraph vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. InfluxDB vs. JanusGraph vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully managed big data interactive analytics platform
Primary database modelDocument store
Key-value store
Document storeTime Series DBMSGraph DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMS infowith GEO packageDocument store infoIf 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 infothis 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 infosupport 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 infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewjanusgraph.orgazure.microsoft.com/­services/­data-explorer
Technical documentationcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbdocs.janusgraph.orgdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAtos Convergence CreatorsGoogleLinux Foundation; originally developed as Titan by AureliusMicrosoft
Initial release20162008201320172019
Current release17032.7.6, April 20240.6.3, February 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava
Server operating systemsLinuxhostedLinux
OS X infothrough Homebrew
Linux
OS X
Unix
Windows
hosted
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalyes, details hereNumeric data and Stringsyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnononoyes
Secondary indexesyesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languagenoKusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Clojure
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnousing Google App EnginenoyesYes, possible languages: KQL, Python, R
TriggersyesCallbacks using the Google Apps Enginenoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infoin enterprise version onlyyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factor infoin enterprise version onlyyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes infovia Faunus, a graph analytics engineSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoDepending on used storage engineno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsUser authentification and security via Rexster Graph ServerAzure Active Directory Authentication
More information provided by the system vendor
Atos Standard Common RepositoryGoogle Cloud DatastoreInfluxDBJanusGraph infosuccessor of TitanMicrosoft Azure Data Explorer
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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