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DBMS > Databricks vs. HBase vs. Lovefield vs. Sequoiadb vs. Spark SQL

System Properties Comparison Databricks vs. HBase vs. Lovefield vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonLovefield  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  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.Wide-column store based on Apache Hadoop and on concepts of BigTableEmbeddable relational database for web apps written in pure JavaScriptNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Wide column storeRelational DBMSDocument store
Relational DBMS
Relational 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
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comhbase.apache.orggoogle.github.io/­lovefieldwww.sequoiadb.comspark.apache.org/­sql
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleSequoiadb Ltd.Apache Software Foundation
Initial release20132008201420132014
Current release2.3.4, January 20212.1.12, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2Open 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 languageJavaJavaScriptC++Scala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesschema-freeyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes infooid, date, timestamp, binary, regexyes
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.yesnononono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language infovia JavaScript builder patternSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavanoJavaScriptno
TriggersyesUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBnono
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnosimple password-based access controlno
More information provided by the system vendor
DatabricksHBaseLovefieldSequoiadbSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseLovefieldSequoiadbSpark SQL
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