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DBMS > Apache Impala vs. Firebase Realtime Database vs. HarperDB vs. Sphinx

System Properties Comparison Apache Impala vs. Firebase Realtime Database vs. HarperDB vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHarperDB  Xexclude from comparisonSphinx  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeDocument storeSearch engine
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
Score14.29
Rank#39  Overall
#6  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgfirebase.google.com/­products/­realtime-databasewww.harperdb.iosphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databasedocs.harperdb.io/­docssphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogle infoacquired by Google 2014HarperDBSphinx Technologies Inc.
Initial release2013201220172001
Current release4.1.0, June 20223.1, August 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree community edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsC++
Server operating systemsLinuxhostedLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesno
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 indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like data manipulation statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCJava
JavaScript
Objective-C
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducelimited functionality with using 'rules'Custom Functions infosince release 3.1no
TriggersnoCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infothe nodes on which a table resides can be definednone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes infoThe original contents of fields are not stored in the Sphinx index.
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 rulesAccess rights for users and rolesno

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Apache ImpalaFirebase Realtime DatabaseHarperDBSphinx
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