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DBMS > Impala vs. QuestDB vs. Sphinx

System Properties Comparison Impala vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameImpala  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA high performance, low latency Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSTime Series DBMSSearch engine
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.15
Rank#37  Overall
#22  Relational DBMS
Score0.28
Rank#266  Overall
#20  Time Series DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Websitewww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlquestdb.iosphinxsearch.com
Technical documentationdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperClouderaQuestDB LimitedSphinx Technologies Inc.
Initial release201320142001
Current release3.3.0, August 20193.2.1, January 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesno
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.nono
Secondary indexesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
HTTP RESTProprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCJavaC++ 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-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenone
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 Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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 Kerberosno
More information provided by the system vendor
ImpalaQuestDBSphinx
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more

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More resources
ImpalaQuestDBSphinx
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