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DBMS > Apache Druid vs. Quasardb vs. Stardog vs. TDengine

System Properties Comparison Apache Druid vs. Quasardb vs. Stardog vs. TDengine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonQuasardb  Xexclude from comparisonStardog  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed, high-performance timeseries databaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTime Series DBMS and big data platform
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSGraph DBMS
RDF store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitedruid.apache.orgquasar.aiwww.stardog.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdruid.apache.org/­docs/­latest/­designdoc.quasar.ai/­masterdocs.stardog.comdocs.tdengine.com
DeveloperApache Software Foundation and contributorsquasardbStardog-UnionTDEngine, previously Taos Data
Initial release2012200920102019
Current release29.0.1, April 20243.14.1, January 20247.3.0, May 20203.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC
Server operating systemsLinux
OS X
Unix
BSD
Linux
OS X
Windows
Linux
macOS
Windows
Linux
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyesyes
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 infoImport/export of XML data possibleno
Secondary indexesyesyes infowith tagsyes infosupports real-time indexing in full-text and geospatialno
SQL infoSupport of SQLSQL for queryingSQL-like query languageYes, compatible with all major SQL variants through dedicated BI/SQL ServerStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
JDBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnonouser defined functions and aggregates, HTTP Server extensions in Javano
Triggersnonoyes infovia event handlersyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoconsistent hashingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replication with selectable replication factorMulti-source replication in HA-Clusteryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemCryptographically strong user authentication and audit trailAccess rights for users and rolesyes
More information provided by the system vendor
Apache DruidQuasardbStardogTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» 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
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More resources
Apache DruidQuasardbStardogTDengine
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