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DBMS > Apache Impala vs. Databricks vs. HBase vs. Sequoiadb vs. Tigris

System Properties Comparison Apache Impala vs. Databricks vs. HBase vs. Sequoiadb vs. Tigris

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionAnalytic 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 SQLA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column storeDocument store
Relational DBMS
Document store
Key-value store
Search engine
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websiteimpala.apache.orgwww.databricks.comhbase.apache.orgwww.sequoiadb.comwww.tigrisdata.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=indexwww.tigrisdata.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.Tigris Data, Inc.
Initial release20132013200820132022
Current release4.1.0, June 20222.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2.0
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 languageC++JavaC++
Server operating systemsLinuxhostedLinux
Unix
Windows infousing Cygwin
LinuxLinux
macOS
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regexyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLnoSQL-like query languageno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSONCLI Client
gRPC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes infoCoprocessors in JavaJavaScriptno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication
Source-replica replication
Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)Document is locked during a transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, using FoundationDB
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, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access controlAccess rights for users and roles
More information provided by the system vendor
Apache ImpalaDatabricksHBaseSequoiadbTigris
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksHBaseSequoiadbTigris
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