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DBMS > Bangdb vs. Databricks vs. HBase vs. Pinecone vs. Sequoiadb

System Properties Comparison Bangdb vs. Databricks vs. HBase vs. Pinecone vs. Sequoiadb

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonPinecone  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe 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 BigTableA managed, cloud-native vector databaseNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Wide column storeVector DBMSDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitebangdb.comwww.databricks.comhbase.apache.orgwww.pinecone.iowww.sequoiadb.com
Technical documentationdocs.bangdb.comdocs.databricks.comhbase.apache.org/­book.htmldocs.pinecone.io/­docs/­overviewwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperSachin Sinha, BangDBDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetPinecone Systems, IncSequoiadb Ltd.
Initial release20122013200820192013
Current releaseBangDB 2.0, October 20212.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache version 2commercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaC++
Server operating systemsLinuxhostedLinux
Unix
Windows infousing Cygwin
hostedLinux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsoptions to bring your own types, AVROString, Number, 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.noyesnonono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesnoyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLnonoSQL-like query language
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
RESTful HTTP APIproprietary protocol using JSON
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Python.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infoCoprocessors in JavaJavaScript
Triggersyes, Notifications (with Streaming only)yesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDSingle row ACID (across millions of columns)Document is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenoyesnono
User concepts infoAccess controlyes (enterprise version only)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
BangdbDatabricksHBasePineconeSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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