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DBMS > CockroachDB vs. Datomic vs. Microsoft Azure Data Explorer vs. Quasardb vs. Riak KV

System Properties Comparison CockroachDB vs. Datomic vs. Microsoft Azure Data Explorer vs. Quasardb vs. Riak KV

Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonDatomic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully managed big data interactive analytics platformDistributed, high-performance timeseries databaseDistributed, fault tolerant key-value store
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitewww.cockroachlabs.comwww.datomic.comazure.microsoft.com/­services/­data-explorerquasar.ai
Technical documentationwww.cockroachlabs.com/­docsdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­masterwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperCockroach LabsCognitectMicrosoftquasardbOpenSource, formerly Basho Technologies
Initial release20152012201920092009
Current release24.1.0, May 20241.0.7075, December 2023cloud service with continuous releases3.14.1, January 20243.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercial infolimited edition freecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache version 2, commercial enterprise edition
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 languageGoJava, ClojureC++Erlang
Server operating systemsLinux
macOS
Windows
All OS with a Java VMhostedBSD
Linux
OS X
Windows
Linux
OS X
Data schemedynamic schemayesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infointeger and binaryno
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.nonoyesnono
Secondary indexesyesyesall fields are automatically indexedyes infowith tagsrestricted
SQL infoSupport of SQLyes, wire compatible with PostgreSQLnoKusto Query Language (KQL), SQL subsetSQL-like query languageno
APIs and other access methodsJDBCRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsYes, possible languages: KQL, Python, RnoErlang
TriggersnoBy using transaction functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTnone 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 replication with selectable replication factorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnoyes infoTransient mode
User concepts infoAccess controlRole-based access controlnoAzure Active Directory AuthenticationCryptographically strong user authentication and audit trailyes, using Riak Security

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More resources
CockroachDBDatomicMicrosoft Azure Data ExplorerQuasardbRiak KV
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