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DBMS > Dragonfly vs. Google Cloud Bigtable vs. Qdrant vs. QuestDB

System Properties Comparison Dragonfly vs. Google Cloud Bigtable vs. Qdrant vs. QuestDB

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQdrant  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high-performance vector database with neural network or semantic-based matchingA high performance open source SQL database for time series data
Primary database modelKey-value storeKey-value store
Wide column store
Vector DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­bigtablegithub.com/­qdrant/­qdrant
qdrant.tech
questdb.io
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­bigtable/­docsqdrant.tech/­documentationquestdb.io/­docs
DeveloperDragonflyDB team and community contributorsGoogleQdrantQuestDB Technology Inc
Initial release2023201520212014
Current release1.0, March 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++RustJava (Zero-GC), C++, Rust
Server operating systemsLinuxhostedDocker
Linux
macOS
Windows
Linux
macOS
Windows
Data schemescheme-freeschema-freeschema-freeyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysnoNumbers, 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.nononono
Secondary indexesnonoyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLnononoSQL with time-series extensions
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresLuanono
Triggerspublish/subscribe channels provide some trigger functionalitynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesCollection-level replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsAtomic single-row operationsACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
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.yesnoyesyes infothrough memory mapped files
User concepts infoAccess controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Key-based authentication
More information provided by the system vendor
DragonflyGoogle Cloud BigtableQdrantQuestDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DragonflyGoogle Cloud BigtableQdrantQuestDB
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