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DBMS > Amazon DocumentDB vs. Apache Impala vs. Databricks vs. HBase vs. Sequoiadb

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. Databricks vs. HBase vs. Sequoiadb

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for HadoopThe 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 BigTableNewSQL database with distributed OLTP and SQL
Primary database modelDocument storeRelational DBMSDocument store
Relational DBMS
Wide column storeDocument store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websiteaws.amazon.com/­documentdbimpala.apache.orgwww.databricks.comhbase.apache.orgwww.sequoiadb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesimpala.apache.org/­impala-docs.htmldocs.databricks.comhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20192013201320082013
Current release4.1.0, June 20222.3.4, January 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemshostedLinuxhostedLinux
Unix
Windows infousing Cygwin
Linux
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes 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.nonoyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementswith Databricks SQLnoSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBCPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes infoCoprocessors in JavaJavaScript
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factoryesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDSingle row ACID (across millions of columns)Document is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
Amazon DocumentDBApache ImpalaDatabricksHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon DocumentDBApache ImpalaDatabricksHBaseSequoiadb
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