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DBMS > Databricks vs. HBase vs. Lovefield vs. Qdrant vs. Sequoiadb

System Properties Comparison Databricks vs. HBase vs. Lovefield vs. Qdrant vs. Sequoiadb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonLovefield  Xexclude from comparisonQdrant  Xexclude from comparisonSequoiadb  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 JavaScriptA high-performance vector database with neural network or semantic-based matchingNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Wide column storeRelational DBMSVector DBMSDocument store
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
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Websitewww.databricks.comhbase.apache.orggoogle.github.io/­lovefieldgithub.com/­qdrant/­qdrant
qdrant.tech
www.sequoiadb.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdqdrant.tech/­documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleQdrantSequoiadb Ltd.
Initial release20132008201420212013
Current release2.3.4, January 20212.1.12, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScriptRustC++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariDocker
Linux
macOS
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesschema-freeschema-free
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesNumbers, Strings, Geo, Booleanyes 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.yesnononono
Secondary indexesyesnoyesyes infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language infovia JavaScript builder patternnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript.Net
Go
Java
JavaScript (Node.js)
Python
Rust
.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 nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneCollection-level replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency, tunable 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 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 MemoryDByesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoKey-based authenticationsimple password-based access control
More information provided by the system vendor
DatabricksHBaseLovefieldQdrantSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHBaseLovefieldQdrantSequoiadb
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