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DBMS > atoti vs. GridGain vs. Microsoft Azure Data Explorer

System Properties Comparison atoti vs. GridGain vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.GridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platform
Primary database modelObject oriented DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument 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
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteatoti.iowww.gridgain.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.atoti.iowww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperActiveViamGridGain Systems, Inc.Microsoft
Initial release20072019
Current releaseGridGain 8.5.1cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .Net
Server operating systemsLinux
OS X
Solaris
Windows
hosted
Data schemeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes 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.yesyes
Secondary indexesyesall fields are automatically indexed
SQL infoSupport of SQLMultidimensional Expressions (MDX)ANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subset
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresPythonyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, R
Triggersyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsAzure Active Directory Authentication

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More resources
atotiGridGainMicrosoft Azure Data Explorer
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