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DBMS > Badger vs. Databricks vs. HBase vs. LevelDB vs. Sequoiadb

System Properties Comparison Badger vs. Databricks vs. HBase vs. LevelDB vs. Sequoiadb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonLevelDB  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The 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 fast key-value storage library that provides an ordered mapping from string keys to string valuesNewSQL database with distributed OLTP and SQL
Primary database modelKey-value storeDocument store
Relational DBMS
Wide column storeKey-value storeDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comhbase.apache.orggithub.com/­google/­leveldbwww.sequoiadb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comhbase.apache.org/­book.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDGraph LabsDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleSequoiadb Ltd.
Initial release20172013200820112013
Current release2.3.4, January 20211.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache version 2Open Source infoBSDOpen 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 languageGoJavaC++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
Unix
Windows infousing Cygwin
Illumos
Linux
OS X
Windows
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROnoyes 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.noyesnonono
Secondary indexesnoyesnonoyes
SQL infoSupport of SQLnowith Databricks SQLnonoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesGoPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infoCoprocessors in JavanoJavaScript
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)noDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnosimple password-based access control
More information provided by the system vendor
BadgerDatabricksHBaseLevelDBSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

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BadgerDatabricksHBaseLevelDBSequoiadb
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