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DBMS > Databricks vs. Heroic vs. Hive vs. Ignite vs. Solr

System Properties Comparison Databricks vs. Heroic vs. Hive vs. Ignite vs. Solr

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHeroic  Xexclude from comparisonHive  Xexclude from comparisonIgnite  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchdata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsSpatial 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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comgithub.com/­spotify/­heroichive.apache.orgignite.apache.orgsolr.apache.org
Technical documentationdocs.databricks.comspotify.github.io/­heroiccwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docssolr.apache.org/­resources.html
DeveloperDatabricksSpotifyApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software Foundation
Initial release20132014201220152006
Current release3.1.3, April 2022Apache Ignite 2.69.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, Java, .NetJava
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
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-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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.yesnoyesyes
Secondary indexesyesyes infovia Elasticsearchyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.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 aggregatesnoyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)Java plugins
Triggersnonoyes (cache interceptors and events)yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factoryes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and rolesSecurity Hooks for custom implementationsyes
More information provided by the system vendor
DatabricksHeroicHiveIgniteSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHeroicHiveIgniteSolr
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