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DBMS > Apache Druid vs. BigchainDB vs. Microsoft Azure Data Explorer vs. Pinecone

System Properties Comparison Apache Druid vs. BigchainDB vs. Microsoft Azure Data Explorer vs. Pinecone

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigchainDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsFully managed big data interactive analytics platformA managed, cloud-native vector database
Primary database modelRelational DBMS
Time Series DBMS
Document storeRelational DBMS infocolumn orientedVector DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Websitedruid.apache.orgwww.bigchaindb.comazure.microsoft.com/­services/­data-explorerwww.pinecone.io
Technical documentationdruid.apache.org/­docs/­latest/­designbigchaindb.readthedocs.io/­en/­latestdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.pinecone.io/­docs/­overview
DeveloperApache Software Foundation and contributorsMicrosoftPinecone Systems, Inc
Initial release2012201620192019
Current release29.0.1, April 2024cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL v3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaPython
Server operating systemsLinux
OS X
Unix
Linuxhostedhosted
Data schemeyes infoschema-less columns are supportedschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesString, Number, Boolean
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.nonoyesno
Secondary indexesyesall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
CLI Client
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Python
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, R
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesAzure Active Directory Authentication

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More resources
Apache DruidBigchainDBMicrosoft Azure Data ExplorerPinecone
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