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DBMS > Apache Druid vs. EJDB vs. Hypertable vs. Interbase vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Druid vs. EJDB vs. Hypertable vs. Interbase vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEJDB  Xexclude from comparisonHypertable  Xexclude from comparisonInterbase  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.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEmbeddable document-store database library with JSON representation of queries (in MongoDB style)An open source BigTable implementation based on distributed file systems such as HadoopLight-weight proven RDBMS infooriginally from BorlandFully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Document storeWide column storeRelational DBMSRelational 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedruid.apache.orggithub.com/­Softmotions/­ejdbwww.embarcadero.com/­products/­interbaseazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.embarcadero.com/­products/­interbasedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsSoftmotionsHypertable Inc.EmbarcaderoMicrosoft
Initial release20122012200919842019
Current release29.0.1, April 20240.9.8.11, March 2016InterBase 2020, December 2019cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGPLv2Open Source infoGNU version 3. Commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++C
Server operating systemsLinux
OS X
Unix
server-lessLinux
OS X
Windows infoan inofficial Windows port is available
Android
iOS
Linux
OS X
Windows
hosted
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idnoyesyes 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.nono infoexport as XML data possibleyes
Secondary indexesyesnorestricted infoonly exact value or prefix value scansyesall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnonoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
in-process shared libraryC++ API
Thrift
ADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnononoyes infoInterbase procedure and trigger languageYes, possible languages: KQL, Python, R
Triggersnononoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneselectable replication factor on file system levelInterbase Change Viewsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes infoMultiversion concurreny controlyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnonofine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache DruidEJDBHypertableInterbaseMicrosoft Azure Data Explorer
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