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DBMS > Apache Pinot vs. Databricks vs. HBase vs. Lovefield vs. Sequoiadb

System Properties Comparison Apache Pinot vs. Databricks vs. HBase vs. Lovefield vs. Sequoiadb

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonLovefield  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyThe 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 SQL
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column storeRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
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
Websitepinot.apache.orgwww.databricks.comhbase.apache.orggoogle.github.io/­lovefieldwww.sequoiadb.com
Technical documentationdocs.pinot.apache.orgdocs.databricks.comhbase.apache.org/­book.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation and contributorsDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleSequoiadb Ltd.
Initial release20152013200820142013
Current release1.0.0, September 20232.3.4, January 20212.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaScriptC++
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infooid, date, timestamp, binary, regex
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.yesnonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLnoSQL-like query language infovia JavaScript builder patternSQL-like query language
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesGo
Java
Python
Python
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavanoJavaScript
TriggersyesUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneSource-replica replication
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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnosimple password-based access control
More information provided by the system vendor
Apache PinotDatabricksHBaseLovefieldSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache PinotDatabricksHBaseLovefieldSequoiadb
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