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DBMS > Hazelcast vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

System Properties Comparison Hazelcast vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionA widely adopted in-memory data gridA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn orientedWide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial 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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitehazelcast.comgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationhazelcast.org/­imdg/­docsdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHazelcastHEAVY.AI, Inc.MicrosoftMicrosoft
Initial release2008201620192012
Current release5.3.6, November 20235.10, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ and CUDA
Server operating systemsAll OS with a Java VMLinuxhostedhosted
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyes 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 infothe object must implement a serialization strategynoyesno
Secondary indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesnoYes, possible languages: KQL, Python, Rno
Triggersyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonooptimistic locking
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 controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signatures

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More resources
HazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerMicrosoft Azure Table Storage
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