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DBMS > Apache Impala vs. Firebase Realtime Database vs. HEAVY.AI

System Properties Comparison Apache Impala vs. Firebase Realtime Database vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websiteimpala.apache.orgfirebase.google.com/­products/­realtime-databasegithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databasedocs.heavy.ai
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogle infoacquired by Google 2014HEAVY.AI, Inc.
Initial release201320122016
Current release4.1.0, June 20225.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDA
Server operating systemsLinuxhostedLinux
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Supported programming languagesAll languages supporting JDBC/ODBCJava
JavaScript
Objective-C
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducelimited functionality with using 'rules'no
TriggersnoCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, based on authentication and database rulesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaFirebase Realtime DatabaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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