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DBMS > DolphinDB vs. QuestDB vs. Vitess

System Properties Comparison DolphinDB vs. QuestDB vs. Vitess

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonQuestDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A high performance open source SQL database for time series dataScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.dolphindb.comquestdb.iovitess.io
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlquestdb.io/­docsvitess.io/­docs
DeveloperDolphinDB, IncQuestDB Technology IncThe Linux Foundation, PlanetScale
Initial release201820142013
Current releasev2.00.4, January 202215.0.2, December 2022
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustGo
Server operating systemsLinux
Windows
Linux
macOS
Windows
Docker
Linux
macOS
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyes
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL with time-series extensionsyes infowith proprietary extensions
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with eventual consistencyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID for single-table writesACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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.yesyes infothrough memory mapped filesyes
User concepts infoAccess controlAdministrators, Users, GroupsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DolphinDBQuestDBVitess
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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23 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
DolphinDBQuestDBVitess
Recent citations in the news

QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

SQL Extensions for Time-Series Data in QuestDB
11 January 2021, Towards Data Science

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

QuestDB Raises $12M in Series A Funding
8 November 2021, FinSMEs

Aquis Exchange goes live with QuestDB for real time monitoring
2 November 2022, FinanceFeeds

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



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