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DBMS > Apache IoTDB vs. Coveo vs. EXASOL vs. Faircom DB vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Coveo vs. EXASOL vs. Faircom DB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCoveo  Xexclude from comparisonEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSSearch engineRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.11
Rank#118  Overall
#11  Search engines
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.coveo.comwww.exasol.comwww.faircom.com/­products/­faircom-dbspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.coveo.comwww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCoveoExasolFairCom CorporationApache Software Foundation
Initial release20182012200019792014
Current release1.1.0, April 2023V12, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoRestricted, free version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++Scala
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languagenoyesyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
RESTful HTTP API.Net
JDBC
ODBC
WebSocket
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Java
JavaScript
Python
Java
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnouser defined functionsyes info.Net, JavaScript, C/C++no
Triggersyesyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynoyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDtunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesgranular access controls, API key management, content filtersAccess rights for users, groups and roles according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesno

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More resources
Apache IoTDBCoveoEXASOLFaircom DB infoformerly c-treeACESpark SQL
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