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DBMS > Datomic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. RethinkDB vs. Sqrrl

System Properties Comparison Datomic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. RethinkDB vs. Sqrrl

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRethinkDB  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platformDBMS for the Web with a mechanism to push updated query results to applications in realtime.Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument storeDocument store
Graph DBMS
Key-value store
Wide column store
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Websitewww.datomic.comwww.leanxcale.comazure.microsoft.com/­services/­data-explorerrethinkdb.comsqrrl.com
Technical documentationdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorerrethinkdb.com/­docs
DeveloperCognitectLeanXcaleMicrosoftThe Linux Foundation infosince July 2017Amazon infooriginally Sqrrl Data, Inc.
Initial release20122015201920092012
Current release1.0.6735, June 2023cloud service with continuous releases2.4.1, August 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++Java
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Linux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infostring, binary, float, bool, date, geometryyes
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.noyesno
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsRESTful HTTP APIJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesClojure
Java
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes infoTransaction FunctionsYes, possible languages: KQL, Python, Rno
TriggersBy using transaction functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceSharding inforange basedSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic single-document operationsAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnono
User concepts infoAccess controlnoAzure Active Directory Authenticationyes infousers and table-level permissionsCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
DatomicLeanXcaleMicrosoft Azure Data ExplorerRethinkDBSqrrl
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