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DBMS > Databricks vs. Ehcache vs. Solr

System Properties Comparison Databricks vs. Ehcache vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonSolr  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 Java cache with tiered storage optionsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Key-value storeSearch engine
Secondary database modelsSpatial 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
Score4.64
Rank#68  Overall
#8  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comwww.ehcache.orgsolr.apache.org
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationsolr.apache.org/­resources.html
DeveloperDatabricksTerracotta Inc, owned by Software AGApache Software Foundation
Initial release201320092006
Current release3.10.0, March 20229.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedAll 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)schema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typing
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
Secondary indexesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheJava API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Java.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava plugins
Triggersyes infoCache Event Listenersyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serveryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoyes
More information provided by the system vendor
DatabricksEhcacheSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheSolr
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