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DBMS > Databricks vs. Datastax Enterprise vs. Solr

System Properties Comparison Databricks vs. Datastax Enterprise vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatastax Enterprise  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.DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Wide column storeSearch engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.80
Rank#60  Overall
#4  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comwww.datastax.com/­products/­datastax-enterprisesolr.apache.org
Technical documentationdocs.databricks.comdocs.datastax.comsolr.apache.org/­resources.html
DeveloperDatabricksDataStaxApache Software Foundation
Initial release201320112006
Current release6.8, April 20209.6.0, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJava
Server operating systemshostedLinux
OS X
All 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 indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statements (CQL); Spark SQLSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Java API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
Triggersyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoAtomicity and isolation are supported for single operationsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users can be defined per objectyes
More information provided by the system vendor
DatabricksDatastax EnterpriseSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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DatabricksDatastax EnterpriseSolr
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