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DBMS > Databricks vs. DataFS vs. Hazelcast vs. Solr vs. TinkerGraph

System Properties Comparison Databricks vs. DataFS vs. Hazelcast vs. Solr vs. TinkerGraph

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDataFS  Xexclude from comparisonHazelcast  Xexclude from comparisonSolr  Xexclude from comparisonTinkerGraph  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.All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A widely adopted in-memory data gridA widely used distributed, scalable search engine based on Apache LuceneA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Relational DBMS
Object oriented DBMSKey-value storeSearch engineGraph DBMS
Secondary database modelsGraph DBMSDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitewww.databricks.comnewdatabase.comhazelcast.comsolr.apache.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.databricks.comdev.mobiland.com/­Overview.xsphazelcast.org/­imdg/­docssolr.apache.org/­resources.html
DeveloperDatabricksMobiland AGHazelcastApache Software Foundation
Initial release20132018200820062009
Current release1.1.263, October 20225.3.6, November 20239.6.0, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemshostedWindowsAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.yesnoyes infothe object must implement a serialization strategyyesno
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languageSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
TinkerPop 3
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Groovy
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor ServicesJava pluginsno
Triggersno, except callback-events from server when changes happenedyes infoEventsyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistencynone
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlWindows-ProfileRole-based access controlyesno
More information provided by the system vendor
DatabricksDataFSHazelcastSolrTinkerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDataFSHazelcastSolrTinkerGraph
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