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DBMS > Apache Impala vs. Databricks vs. Firebase Realtime Database vs. Hypertable vs. NuoDB

System Properties Comparison Apache Impala vs. Databricks vs. Firebase Realtime Database vs. Hypertable vs. NuoDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHypertable  Xexclude from comparisonNuoDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.An open source BigTable implementation based on distributed file systems such as HadoopNuoDB is a webscale distributed database that supports SQL and ACID transactions
Primary database modelRelational DBMSDocument store
Relational DBMS
Document storeWide column storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score15.00
Rank#39  Overall
#6  Document stores
Score0.99
Rank#195  Overall
#92  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comfirebase.google.com/­products/­realtime-databasewww.3ds.com/­nuodb-distributed-sql-database
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comfirebase.google.com/­docs/­databasedoc.nuodb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksGoogle infoacquired by Google 2014Hypertable Inc.Dassault Systèmes infooriginally NuoDB, Inc.
Initial release20132013201220092013
Current release4.1.0, June 20220.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoGNU version 3. Commercial license availablecommercial infolimited edition free
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++
Server operating systemsLinuxhostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
hosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesnono
Secondary indexesyesyesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLnonoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
C++ API
Thrift
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
Java
JavaScript
Objective-C
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregateslimited functionality with using 'rules'noJava, SQL
TriggersnoCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingdata is dynamically stored/cached on the nodes where it is read/written
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factor on file system levelyes infoManaged transparently by NuoDB
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesnoACID infotunable commit protocol
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoMVCC
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.nonoyes infoTemporary table
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, based on authentication and database rulesnoStandard SQL roles/ privileges, Administrative Users
More information provided by the system vendor
Apache ImpalaDatabricksFirebase Realtime DatabaseHypertableNuoDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksFirebase Realtime DatabaseHypertableNuoDB
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