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DBMS > Drizzle vs. HarperDB vs. Kinetica vs. Microsoft Azure Data Explorer

System Properties Comparison Drizzle vs. HarperDB vs. Kinetica vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score0.55
Rank#252  Overall
#38  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.harperdb.iowww.kinetica.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.harperdb.io/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDrizzle project, originally started by Brian AkerHarperDBKineticaMicrosoft
Initial release2008201720122019
Current release7.2.4, September 20123.1, August 20217.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsC, C++
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Linuxhosted
Data schemeyesdynamic schemayesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like data manipulation statementsSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1user defined functionsYes, possible languages: KQL, Python, R
Triggersno infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definedSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and rolesAccess rights for users and roles on table levelAzure Active Directory Authentication

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More resources
DrizzleHarperDBKineticaMicrosoft Azure Data Explorer
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