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DBMS > Apache Impala vs. Brytlyt vs. Firebase Realtime Database

System Properties Comparison Apache Impala vs. Brytlyt vs. Firebase Realtime Database

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.
Primary database modelRelational DBMSRelational DBMSDocument store
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
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score15.00
Rank#39  Overall
#6  Document stores
Websiteimpala.apache.orgbrytlyt.iofirebase.google.com/­products/­realtime-database
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iofirebase.google.com/­docs/­database
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytGoogle infoacquired by Google 2014
Initial release201320162012
Current release4.1.0, June 20225.0, August 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and CUDA
Server operating systemsLinuxLinux
OS X
Windows
hosted
Data schemeyesyesschema-free
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.noyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java
JavaScript
Objective-C
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLlimited functionality with using 'rules'
TriggersnoyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica 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 ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes
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.no
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyes, based on authentication and database rules

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More resources
Apache ImpalaBrytlytFirebase Realtime Database
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Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
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1 August 2023, PR Newswire

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22 December 2021, Silicon Canals

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

Brytlyt becomes NVIDIA Inception Premier Partner
31 January 2023, PR Newswire

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

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