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DBMS > Apache Pinot vs. Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Pinot vs. Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS infocolumn oriented
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
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websitepinot.apache.orgcloud.google.com/­datastorewww.hawkular.orgazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.pinot.apache.orgcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsGoogleCommunity supported by Red HatMicrosoft
Initial release2015200820142019
Current release1.0.0, September 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
OS X
Windows
hosted
Data schemeyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes, details hereyesyes 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 indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like query language (GQL)noKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresusing Google App EnginenoYes, possible languages: KQL, Python, R
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infobased on CassandraSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAzure Active Directory Authentication

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More resources
Apache PinotGoogle Cloud DatastoreHawkular MetricsMicrosoft Azure Data Explorer
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