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DBMS > Faircom DB vs. Hive vs. Spark SQL vs. SwayDB vs. TimescaleDB

System Properties Comparison Faircom DB vs. Hive vs. Spark SQL vs. SwayDB vs. TimescaleDB

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.data warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMSKey-value storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.faircom.com/­products/­faircom-dbhive.apache.orgspark.apache.org/­sqlswaydb.simer.auwww.timescale.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperFairCom CorporationApache Software Foundation infoinitially developed by FacebookApache Software FoundationSimer PlahaTimescale
Initial release19792012201420182017
Current releaseV12, November 20203.1.3, April 20223.5.0 ( 2.13), September 20232.13.0, November 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGNU Affero GPL V3.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaScalaScalaC
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
All OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesyesschema-freeyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Thrift
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C++
Java
PHP
Python
Java
Python
R
Scala
Java
Kotlin
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infouser defined functions and integration of map-reducenonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark Corenoneyes, across time and space (hash partitioning) attributes
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 factornonenoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnonoAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and rolesnonofine grained access rights according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACEHiveSpark SQLSwayDBTimescaleDB
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