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DBMS > EJDB vs. HEAVY.AI vs. Hypertable vs. Microsoft Azure Data Explorer

System Properties Comparison EJDB vs. HEAVY.AI vs. Hypertable vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platform
Primary database modelDocument storeRelational DBMSWide column storeRelational 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
Score0.27
Rank#297  Overall
#44  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSoftmotionsHEAVY.AI, Inc.Hypertable Inc.Microsoft
Initial release2012201620092019
Current release5.10, January 20220.9.8.11, March 2016cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++ and CUDAC++
Server operating systemsserver-lessLinuxLinux
OS X
Windows infoan inofficial Windows port is available
hosted
Data schemeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesnoyes 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.noyes
Secondary indexesnonorestricted infoonly exact value or prefix value scansall fields are automatically indexed
SQL infoSupport of SQLnoyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsin-process shared libraryJDBC
ODBC
Thrift
Vega
C++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnononoYes, possible languages: KQL, Python, R
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoRound robinShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark 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 integrityno infotypically not needed, however similar functionality with collection joins possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
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.yesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAzure Active Directory Authentication

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More resources
EJDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HypertableMicrosoft Azure Data Explorer
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