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DBMS > Apache Pinot vs. CrateDB vs. Microsoft Azure Table Storage vs. SAP HANA

System Properties Comparison Apache Pinot vs. CrateDB vs. Microsoft Azure Table Storage vs. SAP HANA

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonCrateDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyDistributed Database based on LuceneA Wide Column Store for rapid development using massive semi-structured datasetsIn-memory, column based data store. Available as appliance or cloud service
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeRelational DBMS
Secondary database modelsRelational DBMSDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score44.69
Rank#22  Overall
#16  Relational DBMS
Websitepinot.apache.orgcratedb.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.sap.com/­products/­hana.html
Technical documentationdocs.pinot.apache.orgcratedb.com/­docshelp.sap.com/­hana
DeveloperApache Software Foundation and contributorsCrateMicrosoftSAP
Initial release2015201320122010
Current release1.0.0, September 20232.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno infoalso available as a cloud based service
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJava
Server operating systemsAll OS with a Java JDK11 or higherAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedAppliance or cloud-service
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesGo
Java
Python
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)noSQLScript, R
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyoptimistic lockingACID
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.nonoyes
User concepts infoAccess controlrights management via user accountsAccess rights based on private key authentication or shared access signaturesyes
More information provided by the system vendor
Apache PinotCrateDBMicrosoft Azure Table StorageSAP HANA
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Apache PinotCrateDBMicrosoft Azure Table StorageSAP HANA
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