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DBMS > Apache Druid vs. EJDB vs. Manticore Search vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison Apache Druid vs. EJDB vs. Manticore Search vs. Microsoft Azure Data Explorer vs. TimesTen

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEJDB  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  Xexclude from comparison
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)Multi-storage database for search, including full-text search.Fully managed big data interactive analytics platformIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMS
Time Series DBMS
Document storeSearch engineRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitedruid.apache.orggithub.com/­Softmotions/­ejdbmanticoresearch.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation and contributorsSoftmotionsManticore SoftwareMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122012201720191998
Current release29.0.1, April 20246.0, February 2023cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGPLv2Open Source infoGPL version 2commercialcommercial
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-lessFreeBSD
Linux
macOS
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyes infoschema-less columns are supportedschema-freeFixed schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes 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.noCan index from XMLyesno
Secondary indexesyesnoyes infofull-text index on all search fieldsall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingnoSQL-like query languageKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
in-process shared libraryBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnonouser defined functionsYes, possible languages: KQL, Python, RPL/SQL
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneSynchronous replication based on Galera libraryyes 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 methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
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 datanonoyes infoisolated transactions for atomic changes and binary logging for safe writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes infoby means of logfiles and checkpoints
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 DruidEJDBManticore SearchMicrosoft Azure Data ExplorerTimesTen
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