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DBMS > Apache IoTDB vs. Brytlyt vs. etcd vs. Ingres vs. Teradata

System Properties Comparison Apache IoTDB vs. Brytlyt vs. etcd vs. Ingres vs. Teradata

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonetcd  Xexclude from comparisonIngres  Xexclude from comparisonTeradata  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 hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelTime Series DBMSRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time 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
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteiotdb.apache.orgbrytlyt.ioetcd.io
github.com/­etcd-io/­etcd
www.actian.com/­databases/­ingreswww.teradata.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.ioetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.actian.com/­ingresdocs.teradata.com
DeveloperApache Software FoundationBrytlytActian CorporationTeradata
Initial release201820161974 infooriginally developed at University Berkely in early 1970s1984
Current release1.1.0, April 20235.0, August 20233.4, August 201911.2, May 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and CUDAGoC
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
hosted
Linux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 availableyes
Secondary indexesyesyesnoyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query languageyesnoyesyes infoSQL 2016 + extensions
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)
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLnoyesyes infoUDFs, stored procedures, table functions in parallel
Triggersyesyesyes, watching key changesyesyes
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 infoHashing
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 ReplicatorMulti-source replication
Source-replica replication
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 integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
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.yesnonoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBBrytlytetcdIngresTeradata
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