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DBMS > Apache IoTDB vs. Brytlyt vs. etcd vs. Ingres vs. SWC-DB

System Properties Comparison Apache IoTDB vs. Brytlyt vs. etcd vs. Ingres vs. SWC-DB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonetcd  Xexclude from comparisonIngres  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 FlinkScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA distributed reliable key-value storeWell established RDBMSA high performance, scalable Wide Column DBMS
Primary database modelTime Series DBMSRelational DBMSKey-value storeRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteiotdb.apache.orgbrytlyt.ioetcd.io
github.com/­etcd-io/­etcd
www.actian.com/­databases/­ingresgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.ioetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.actian.com/­ingres
DeveloperApache Software FoundationBrytlytActian CorporationAlex Kashirin
Initial release201820161974 infooriginally developed at University Berkely in early 1970s2020
Current release1.1.0, April 20235.0, August 20233.4, August 201911.2, May 20220.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAGoCC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
FreeBSD
Linux
Windows infoexperimental
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyes infospecific XML-type available, but no XML query functionality.nono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesnoyesSQL-like query language
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JSON over HTTP
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary protocol
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C++
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLnoyesno
Triggersyesyesyes, watching key changesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Ingres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Apache IoTDBBrytlytetcdIngresSWC-DB infoSuper Wide Column Database
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