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DBMS > etcd vs. Spark SQL vs. Teradata vs. TimescaleDB vs. Transbase

System Properties Comparison etcd vs. Spark SQL vs. Teradata vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA distributed reliable key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value storeRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sqlwww.teradata.comwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comdocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationTeradataTimescaleTransaction Software GmbH
Initial release2014198420171987
Current release3.4, August 20193.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 20192.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoApache 2.0commercial infofree development license
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 languageGoScalaCC and C++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
hosted
Linux
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesyesno
Secondary indexesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyes infoUDFs, stored procedures, table functions in paralleluser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyes, watching key changesnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoHashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.noneMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesnono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
etcdSpark SQLTeradataTimescaleDBTransbase
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