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DBMS > Apache Pinot vs. LevelDB vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

System Properties Comparison Apache Pinot vs. LevelDB vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSKey-value storeRelational DBMS infocolumn orientedWide 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitepinot.apache.orggithub.com/­google/­leveldbazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.pinot.apache.orggithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsGoogleMicrosoftMicrosoft
Initial release2015201120192012
Current release1.0.0, September 20231.23, February 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsAll OS with a Java JDK11 or higherIllumos
Linux
OS X
Windows
hostedhosted
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesnoyes 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.noyesno
Secondary indexesnoall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signatures

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More resources
Apache PinotLevelDBMicrosoft Azure Data ExplorerMicrosoft Azure Table Storage
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