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DBMS > Apache Druid vs. DolphinDB vs. eXtremeDB vs. SingleStore vs. Vertica

System Properties Comparison Apache Druid vs. DolphinDB vs. eXtremeDB vs. SingleStore vs. Vertica

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDolphinDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDolphinDB 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.Natively in-memory DBMS with options for persistency, high-availability and clusteringMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeCloud 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 DBMS
Time Series DBMS
Time Series DBMS
Vector DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score2.72
Rank#100  Overall
#8  Time Series DBMS
#5  Vector DBMS
Score0.79
Rank#212  Overall
#100  Relational DBMS
#18  Time Series DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitedruid.apache.orgwww.dolphindb.comwww.mcobject.comwww.singlestore.comwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.dolphindb.cn/­en/­help200/­index.htmlwww.mcobject.com/­docs/­extremedb.htmdocs.singlestore.comvertica.com/­documentation
DeveloperApache Software Foundation and contributorsDolphinDB, IncMcObjectSingleStore Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122018200120132005
Current release30.0.0, June 2024v2.00.4, January 20228.2, 20218.5, January 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community version availablecommercialcommercial infofree developer edition availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C and C++C++, GoC++
Server operating systemsLinux
OS X
Unix
Linux
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux info64 bit version requiredLinux
Data schemeyes infoschema-less columns are supportedyesyesyesYes, 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 dateyesyesyesyesyes
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 infosupport of XML interfaces availablenono
Secondary indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingSQL-like query languageyes infowith the option: eXtremeSQLyes infobut no triggers and foreign keysFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
C
C#
C++
Java
Lua
Python
Scala
Bash
C
C#
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infoby defining eventsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioninghorizontal partitioning / shardingSharding infohash partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Source-replica replication infostores two copies of each physical data partition on two separate nodesMulti-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 methodsnoyesnono infocan define user-defined aggregate functions for map-reduce-style calculationsno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAdministrators, Users, GroupsFine grained access control via users, groups and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache DruidDolphinDBeXtremeDBSingleStore infoformer name was MemSQLVertica infoOpenText™ Vertica™
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