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

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

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonKeyDB  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeKey-value 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
Score0.27
Rank#297  Overall
#44  Document stores
Score0.71
Rank#226  Overall
#33  Key-value 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
Websitegithub.com/­Softmotions/­ejdbgithub.com/­Snapchat/­KeyDB
keydb.dev
manticoresearch.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.keydb.devmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperSoftmotionsEQ Alpha Technology Ltd.Manticore SoftwareMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122019201720191998
Current release6.0, February 2023cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoBSD-3Open 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 languageCC++C++
Server operating systemsserver-lessLinuxFreeBSD
Linux
macOS
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeFixed schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idpartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesInt, 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 indexesnoyes infoby using the Redis Search moduleyes infofull-text index on all search fieldsall fields are automatically indexedyes
SQL infoSupport of SQLnonoSQL-like query languageKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsin-process shared libraryProprietary protocol infoRESP - REdis Serialization ProtocoBinary 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 languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
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 proceduresnoLuauser 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 nodesnoneShardingSharding 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 nodesnoneMulti-source replication
Source-replica replication
Synchronous 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 systemEventual Consistency
Strong eventual consistency with CRDTs
Eventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoOptimistic locking, atomic execution of commands blocks and scriptsyes infoisolated transactions for atomic changes and binary logging for safe writesnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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.yesnoyes
User concepts infoAccess controlnosimple password-based access control and ACLnoAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
EJDBKeyDBManticore SearchMicrosoft Azure Data ExplorerTimesTen
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