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DBMS > Apache Drill vs. DolphinDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. PlanetScale

System Properties Comparison Apache Drill vs. DolphinDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. PlanetScale

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonDolphinDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelDocument store
Relational DBMS
Time Series DBMS
Vector DBMS
Graph DBMS
Key-value store
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsRelational DBMSDocument 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#126  Overall
#23  Document stores
#60  Relational DBMS
Score2.72
Rank#100  Overall
#8  Time Series DBMS
#5  Vector DBMS
Score0.56
Rank#241  Overall
#21  Graph DBMS
#34  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.09
Rank#178  Overall
#82  Relational DBMS
Websitedrill.apache.orgwww.dolphindb.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorerplanetscale.com
Technical documentationdrill.apache.org/­docsdocs.dolphindb.cn/­en/­help200/­index.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerplanetscale.com/­docs
DeveloperApache Software FoundationDolphinDB, IncMicrosoftMicrosoftPlanetScale
Initial release20122018201020192020
Current release1.20.3, January 2023v2.00.4, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community version availableOpen Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++.NET and CGo
Server operating systemsLinux
OS X
Windows
Linux
Windows
.NEThostedDocker
Linux
macOS
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyes
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like query languagenoKusto Query Language (KQL), SQL subsetyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsyesyesYes, possible languages: KQL, Python, Ryes infoproprietary syntax
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentDepending on the underlying data sourceyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesyesnoyes
User concepts infoAccess controlDepending on the underlying data sourceAdministrators, Users, GroupsAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache DrillDolphinDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerPlanetScale
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