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DBMS > Apache Pinot vs. Faircom DB vs. InfluxDB vs. Spark SQL

System Properties Comparison Apache Pinot vs. Faircom DB vs. InfluxDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonInfluxDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.DBMS for storing time series, events and metricsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgwww.faircom.com/­products/­faircom-dbwww.influxdata.com/­products/­influxdb-overviewspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.influxdata.com/­influxdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsFairCom CorporationApache Software Foundation
Initial release2015197920132014
Current release1.0.0, September 2023V12, November 20202.7.6, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++GoScala
Server operating systemsAll OS with a Java JDK11 or higherAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X infothrough Homebrew
Linux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresNumeric data and Stringsyes
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 indexesyesnono
SQL infoSupport of SQLSQL-like query languageyes, ANSI SQL with proprietary extensionsSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP API
JSON over UDP
JDBC
ODBC
Supported programming languagesGo
Java
Python
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++nono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoin enterprise version onlyyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).selectable replication factor infoin enterprise version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually Consistentnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoDepending on used storage engineno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filessimple rights management via user accountsno
More information provided by the system vendor
Apache PinotFaircom DB infoformerly c-treeACEInfluxDBSpark SQL
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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