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DBMS > Databricks vs. Hazelcast

System Properties Comparison Databricks vs. Hazelcast

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHazelcast  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 grid
Primary database modelDocument store
Relational DBMS
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Websitewww.databricks.comhazelcast.com
Technical documentationdocs.databricks.comhazelcast.org/­imdg/­docs
DeveloperDatabricksHazelcast
Initial release20132008
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyes
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 strategy
Secondary indexesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor Services
Triggersyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlRole-based access control
More information provided by the system vendor
DatabricksHazelcast
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHazelcast
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