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DBMS > Databricks vs. Hazelcast vs. Spark SQL vs. Sphinx

System Properties Comparison Databricks vs. Hazelcast vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  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 gridSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comhazelcast.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.databricks.comhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperDatabricksHazelcastApache Software FoundationSphinx Technologies Inc.
Initial release2013200820142001
Current release5.3.6, November 20233.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesno
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 strategyno
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor Servicesnono
Triggersyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 controlnono
More information provided by the system vendor
DatabricksHazelcastSpark SQLSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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