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DBMS > Spark SQL vs. TDengine vs. Vertica

System Properties Comparison Spark SQL vs. TDengine vs. Vertica

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTDengine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS and big data platformCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­taosdata/­TDengine
tdengine.com
www.vertica.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tdengine.comvertica.com/­documentation
DeveloperApache Software FoundationTDEngine, previously Taos DataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201420192005
Current release3.5.0 ( 2.13), September 20233.0, August 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL V3, also commercial editions availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaCC++
Server operating systemsLinux
OS X
Windows
Linux
Windows
Linux
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsStandard SQL with extensions for time-series applicationsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
JDBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, via alarm monitoringyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Spark SQLTDengineVertica infoOpenText™ Vertica™
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
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Cost-based models and subscription-based models are both available. One license is...
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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
Spark SQLTDengineVertica infoOpenText™ Vertica™
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