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DBMS > Cubrid vs. Sphinx vs. TDengine vs. Vertica vs. YDB

System Properties Comparison Cubrid vs. Sphinx vs. TDengine vs. Vertica vs. YDB

Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonSphinx  Xexclude from comparisonTDengine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPOpen source search engine for searching in data from different sources, e.g. relational databasesTime 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.A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSSearch engineTime Series DBMSRelational DBMS infoColumn orientedDocument store
Relational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
sphinxsearch.comgithub.com/­taosdata/­TDengine
tdengine.com
www.vertica.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationcubrid.org/­manualssphinxsearch.com/­docsdocs.tdengine.comvertica.com/­documentationydb.tech/­en/­docs
DeveloperCUBRID Corporation, CUBRID FoundationSphinx Technologies Inc.TDEngine, previously Taos DataOpenText infopreviously Micro Focus and Hewlett PackardYandex
Initial release20082001201920052019
Current release11.0, January 20213.5.1, February 20233.0, August 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL V3, also commercial editions availablecommercial infoLimited community edition freeOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaC++CC++
Server operating systemsLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Windows
LinuxLinux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.Flexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononono
Secondary indexesyesyes infofull-text index on all search fieldsnoNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLyesSQL-like query language (SphinxQL)Standard SQL with extensions for time-series applicationsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.SQL-like query language (YQL)
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
Proprietary protocolJDBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersyesnoyes, via alarm monitoringyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShardinghorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Active-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashAccess rights defined for Yandex Cloud users
More information provided by the system vendor
CubridSphinxTDengineVertica infoOpenText™ Vertica™YDB
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
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...
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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Comprehensive Comparison Between TDengine and TimescaleDB
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Mastering Memory Leak Detection in TDengine
31 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
CubridSphinxTDengineVertica infoOpenText™ Vertica™YDB
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