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DBMS > Hawkular Metrics vs. Hazelcast vs. Kinetica vs. Microsoft Azure Data Explorer vs. Sqrrl

System Properties Comparison Hawkular Metrics vs. Hazelcast vs. Kinetica vs. Microsoft Azure Data Explorer vs. Sqrrl

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  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.
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A widely adopted in-memory data gridFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSKey-value storeRelational DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial 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
Score0.07
Rank#366  Overall
#38  Time Series DBMS
Score7.66
Rank#54  Overall
#5  Key-value stores
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score5.82
Rank#65  Overall
#37  Relational DBMS
Websitewww.hawkular.orghazelcast.comwww.kinetica.comazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehazelcast.org/­imdg/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCommunity supported by Red HatHazelcastKineticaMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release20142008201220192012
Current release5.3.6, November 20237.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial
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 languageJavaJavaC, C++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxhostedLinux
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyes infothe object must implement a serialization strategynoyes
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsHTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesuser defined functionsYes, possible languages: KQL, Python, Rno
Triggersyes infovia Hawkular Alertingyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes infoReplicated MapSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednonoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoRole-based access controlAccess rights for users and roles on table levelAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Hawkular MetricsHazelcastKineticaMicrosoft Azure Data ExplorerSqrrl
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