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DBMS > Apache Impala vs. Firebase Realtime Database vs. Hypertable vs. IRONdb vs. Sphinx

System Properties Comparison Apache Impala vs. Firebase Realtime Database vs. Hypertable vs. IRONdb vs. Sphinx

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHypertable  Xexclude from comparisonIRONdb  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.An open source BigTable implementation based on distributed file systems such as HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeWide column storeTime Series DBMSSearch 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
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgfirebase.google.com/­products/­realtime-databasewww.circonus.com/solutions/time-series-database/sphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databasedocs.circonus.com/irondb/category/getting-startedsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogle infoacquired by Google 2014Hypertable Inc.Circonus LLC.Sphinx Technologies Inc.
Initial release20132012200920172001
Current release4.1.0, June 20220.9.8.11, March 2016V0.10.20, January 20183.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C and C++C++
Server operating systemsLinuxhostedLinux
OS X
Windows infoan inofficial Windows port is available
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes infotext, numeric, histogramsno
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 indexesyesyesrestricted infoonly exact value or prefix value scansnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
C++ API
Thrift
HTTP APIProprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCJava
JavaScript
Objective-C
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
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'noyes, in Luano
TriggersnoCallbacks are triggered when data changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor on file system levelconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
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 ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, based on authentication and database rulesnonono

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Apache ImpalaFirebase Realtime DatabaseHypertableIRONdbSphinx
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