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

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

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEJDB  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata  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 HadoopFully managed big data interactive analytics platformA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS
Time Series DBMS
Document storeWide column storeRelational 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
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedruid.apache.orggithub.com/­Softmotions/­ejdbazure.microsoft.com/­services/­data-explorerwww.teradata.com
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.teradata.com
DeveloperApache Software Foundation and contributorsSoftmotionsHypertable Inc.MicrosoftTeradata
Initial release20122012200920191984
Current release29.0.1, April 20240.9.8.11, March 2016cloud service with continuous releasesTeradata Vantage 1.0 MU2, January 2019
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 servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemsLinux
OS X
Unix
server-lessLinux
OS X
Windows infoan inofficial Windows port is available
hostedhosted
Linux
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idnoyes 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.noyesyes
Secondary indexesyesnorestricted infoonly exact value or prefix value scansall fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL for queryingnonoKusto Query Language (KQL), SQL subsetyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
in-process shared libraryC++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnononoYes, possible languages: KQL, Python, Ryes infoUDFs, stored procedures, table functions in parallel
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingSharding infoImplicit feature of the cloud serviceSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneselectable replication factor on file system levelyes 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 methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnonoAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Apache DruidEJDBHypertableMicrosoft Azure Data ExplorerTeradata
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