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DBMS > QuestDB vs. Spark SQL vs. TDengine vs. Teradata

System Properties Comparison QuestDB vs. Spark SQL vs. TDengine vs. Teradata

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Editorial information provided by DB-Engines
NameQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDengine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS and big data platformA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSRelational DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitequestdb.iospark.apache.org/­sqlgithub.com/­taosdata/­TDengine
tdengine.com
www.teradata.com
Technical documentationquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tdengine.comdocs.teradata.com
DeveloperQuestDB Technology IncApache Software FoundationTDEngine, previously Taos DataTeradata
Initial release2014201420191984
Current release3.5.0 ( 2.13), September 20233.0, August 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPL V3, also commercial editions availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava (Zero-GC), C++, RustScalaC
Server operating systemsLinux
macOS
Windows
Linux
OS X
Windows
Linux
Windows
hosted
Linux
Data schemeyes infoschema-free via InfluxDB Line Protocolyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes
Secondary indexesnononoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL with time-series extensionsSQL-like DML and DDL statementsStandard SQL with extensions for time-series applicationsyes infoSQL 2016 + extensions
APIs and other access methodsHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
JDBC
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnononoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes, via alarm monitoringyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by timestamps)yes, utilizing Spark CoreShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with eventual consistencynoneyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID for single-table writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infothrough memory mapped filesnoyes
User concepts infoAccess controlnoyesfine grained access rights according to SQL-standard
More information provided by the system vendor
QuestDBSpark SQLTDengineTeradata
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
TDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
News

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22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
QuestDBSpark SQLTDengineTeradata
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