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DBMS > Graphite vs. Microsoft Azure AI Search vs. QuestDB

System Properties Comparison Graphite vs. Microsoft Azure AI Search vs. QuestDB

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Editorial information provided by DB-Engines
NameGraphite  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperSearch-as-a-service for web and mobile app developmentA high performance open source SQL database for time series data
Primary database modelTime Series DBMSSearch engineTime Series DBMS
Secondary database modelsVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.75
Rank#75  Overall
#5  Time Series DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Websitegithub.com/­graphite-project/­graphite-webazure.microsoft.com/­en-us/­services/­searchquestdb.io
Technical documentationgraphite.readthedocs.iolearn.microsoft.com/­en-us/­azure/­searchquestdb.io/­docs
DeveloperChris DavisMicrosoftQuestDB Technology Inc
Initial release200620152014
Current releaseV1
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonJava (Zero-GC), C++, Rust
Server operating systemsLinux
Unix
hostedLinux
macOS
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateNumeric data onlyyesyes
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 indexesnoyesno
SQL infoSupport of SQLnonoSQL with time-series extensions
APIs and other access methodsHTTP API
Sockets
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesJavaScript (Node.js)
Python
C#
Java
JavaScript
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud serviceSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayes infolockingyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped files
User concepts infoAccess controlnoyes infousing Azure authentication
More information provided by the system vendor
GraphiteMicrosoft Azure AI SearchQuestDB
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
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The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
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