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DBMS > Apache IoTDB vs. Databend vs. FoundationDB vs. Sphinx

System Properties Comparison Apache IoTDB vs. Databend vs. FoundationDB vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabend  Xexclude from comparisonFoundationDB  Xexclude from comparisonSphinx  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
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 FlinkAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityOrdered key-value store. Core features are complimented by layers.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteiotdb.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
github.com/­apple/­foundationdbsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.comapple.github.io/­foundationdbsphinxsearch.com/­docs
DeveloperApache Software FoundationDatabend LabsFoundationDBSphinx Technologies Inc.
Initial release2018202120132001
Current release1.1.0, April 20231.0.59, April 20236.2.28, November 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaRustC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingno
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 indexesyesnonoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyessupported in specific SQL layer onlySQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
CLI Client
JDBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnoin SQL-layer onlyno
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyLinearizable consistency
Foreign keys infoReferential integritynonoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yes
User concepts infoAccess controlyesUsers with fine-grained authorization concept, user rolesnono

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More resources
Apache IoTDBDatabendFoundationDBSphinx
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