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DBMS > Apache Druid vs. Drizzle vs. Qdrant vs. TDengine

System Properties Comparison Apache Druid vs. Drizzle vs. Qdrant vs. TDengine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDrizzle  Xexclude from comparisonQdrant  Xexclude from comparisonTDengine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A high-performance vector database with neural network or semantic-based matchingTime Series DBMS and big data platform
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSVector DBMSTime 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
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitedruid.apache.orggithub.com/­qdrant/­qdrant
qdrant.tech
github.com/­taosdata/­TDengine
tdengine.com
Technical documentationdruid.apache.org/­docs/­latest/­designqdrant.tech/­documentationdocs.tdengine.com
DeveloperApache Software Foundation and contributorsDrizzle project, originally started by Brian AkerQdrantTDEngine, previously Taos Data
Initial release2012200820212019
Current release29.0.1, April 20247.2.4, September 20123.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGNU GPLOpen Source infoApache Version 2.0Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++RustC
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
OS X
Docker
Linux
macOS
Windows
Linux
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumbers, Strings, Geo, Booleanyes
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
Secondary indexesyesyesyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLSQL for queryingyes infowith proprietary extensionsnoStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnonono
Triggersnono infohooks for callbacks inside the server can be used.yes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Collection-level replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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.noyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemPluggable authentication mechanisms infoe.g. LDAP, HTTPKey-based authenticationyes
More information provided by the system vendor
Apache DruidDrizzleQdrantTDengine
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
News

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 2024

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More resources
Apache DruidDrizzleQdrantTDengine
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