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DBMS > atoti vs. FatDB vs. Microsoft Azure Data Explorer vs. Splice Machine

System Properties Comparison atoti vs. FatDB vs. Microsoft Azure Data Explorer vs. Splice Machine

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplice Machine  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Fully managed big data interactive analytics platformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelObject oriented DBMSDocument store
Key-value store
Relational DBMS infocolumn orientedRelational DBMS
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
Score0.45
Rank#253  Overall
#13  Object oriented DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteatoti.ioazure.microsoft.com/­services/­data-explorersplicemachine.com
Technical documentationdocs.atoti.iodocs.microsoft.com/­en-us/­azure/­data-explorersplicemachine.com/­how-it-works
DeveloperActiveViamFatCloudMicrosoftSplice Machine
Initial release201220192014
Current releasecloud service with continuous releases3.1, March 2021
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Java
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yes
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-typesyes
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.yes
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)no infoVia inetgration in SQL ServerKusto Query Language (KQL), SQL subsetyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes infovia applicationsYes, possible languages: KQL, Python, Ryes infoJava
Triggersyes infovia applicationsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
atotiFatDBMicrosoft Azure Data ExplorerSplice Machine
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