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DBMS > Atos Standard Common Repository vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. Vertica

System Properties Comparison Atos Standard Common Repository vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. Vertica

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVertica infoVertica Analytics Platform  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 networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully managed big data interactive analytics platformCloud or on-premises analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infocolumn orientedRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Search engine
Document 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)
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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#175  Overall
#30  Document stores
#6  Object oriented DBMS
Score7.54
Rank#58  Overall
#34  Relational DBMS
Score19.29
Rank#38  Overall
#24  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comazure.microsoft.com/­services/­data-explorerwww.vertica.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperAtos Convergence CreatorsGigaspaces TechnologiesMicrosoftMicro Focus infoprior to that Hewlett Packard
Initial release2016200020192005
Current release170315.5, September 2020cloud service with continuous releases11.1, February 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageJavaJava, C++, .NetC++
Server operating systemsLinuxLinux
macOS
Solaris
Windows
hostedLinux
Data schemeSchema and schema-less with LDAP viewsschema-freeFixed schema with schema-less datatypes (dynamic)yes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateoptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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.yesno infoXML can be used for describing objects metadatayesno
Secondary indexesyesyesall fields are automatically indexedNo Indexes Required
SQL infoSupport of SQLnoSQL-99 for query and DML statementsKusto Query Language (KQL), SQL subsetFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsLDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages with LDAP bindings.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Ryes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, event driven architectureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlLDAP bind authenticationRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Atos Standard Common RepositoryGigaSpacesMicrosoft Azure Data ExplorerVertica infoVertica Analytics Platform
Specific characteristicsGigaSpaces, the pioneer of In-Memory Computing , drives enterprise digital transformation...
» more
Azure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantages​ AI Driven Autonomous Operations – GigaSpaces’ unique AI driven technology simplifies...
» more
Kusto Query Language (innovative query language, optimized for high performance data...
» more
Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosApplication Acceleration, Smart Caching, BI Acceleration on Fresh Data, Digital Integration...
» more
IoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersMorgan Stanley, Bank of America, Goldman Sachs, PriceRunner, Cerner, Societe Generale,...
» more
Microsoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsForrester has positioned GigaSpaces as a strong performer in The Forrester Wave™:...
» more
Azure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more
Licensing and pricing modelsGigaSpaces offers both open source and commercial editions with annual subscriptions....
» more
An Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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Atos Standard Common RepositoryGigaSpacesMicrosoft Azure Data ExplorerVertica infoVertica Analytics Platform
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