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DBMS > Databricks vs. Hazelcast vs. Linter vs. Microsoft Azure Table Storage

System Properties Comparison Databricks vs. Hazelcast vs. Linter vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A widely adopted in-memory data gridRDBMS for high security requirementsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSWide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.03
Rank#368  Overall
#156  Relational DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Websitewww.databricks.comhazelcast.comlinter.ruazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.databricks.comhazelcast.org/­imdg/­docs
DeveloperDatabricksHazelcastrelex.ruMicrosoft
Initial release2013200819902012
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemshostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.yesyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated MapSource-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 methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
DatabricksHazelcastLinterMicrosoft Azure Table Storage
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHazelcastLinterMicrosoft Azure Table Storage
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