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DBMS > DolphinDB vs. Spark SQL vs. Vertica vs. VictoriaMetrics

System Properties Comparison DolphinDB vs. Spark SQL vs. Vertica vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonVictoriaMetrics  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.Spark SQL is a component on top of 'Spark Core' for structured data processingCloud 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 fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.dolphindb.comspark.apache.org/­sqlwww.vertica.comvictoriametrics.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperDolphinDB, IncApache Software FoundationOpenText infopreviously Micro Focus and Hewlett PackardVictoriaMetrics
Initial release2018201420052018
Current releasev2.00.4, January 20223.5.0 ( 2.13), September 202312.0.3, January 2023v1.91, May 2023
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache 2.0commercial infoLimited community edition freeOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++Go
Server operating systemsLinux
Windows
Linux
OS X
Windows
LinuxFreeBSD
Linux
macOS
OpenBSD
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.nononono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnoyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnonoyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark Corehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDno
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.yesnonono
User concepts infoAccess controlAdministrators, Users, Groupsnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DolphinDBSpark SQLVertica infoOpenText™ Vertica™VictoriaMetrics
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
DolphinDBSpark SQLVertica infoOpenText™ Vertica™VictoriaMetrics
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