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DBMS > Datomic vs. Graph Engine vs. HEAVY.AI vs. Microsoft Azure Data Explorer

System Properties Comparison Datomic vs. Graph Engine vs. HEAVY.AI vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platform
Primary database modelRelational DBMSGraph DBMS
Key-value store
Relational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMSDocument 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.datomic.comwww.graphengine.iogithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorer
Technical documentationdocs.datomic.comwww.graphengine.io/­docs/­manualdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCognitectMicrosoftHEAVY.AI, Inc.Microsoft
Initial release2012201020162019
Current release1.0.6735, June 20235.10, January 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, Clojure.NET and CC++ and CUDA
Server operating systemsAll OS with a Java VM.NETLinuxhosted
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyes
Secondary indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLnonoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
Java
C#
C++
F#
Visual Basic
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoTransaction FunctionsyesnoYes, possible languages: KQL, Python, R
TriggersBy using transaction functionsnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioningSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
DatomicGraph Engine infoformer name: TrinityHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data Explorer
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