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

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

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 comparisonScyllaDB  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 platformCassandra and DynamoDB compatible wide column store
Primary database modelDocument store
Relational DBMS
Time Series DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedWide column store
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
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Websitedrill.apache.orgwww.dolphindb.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorerwww.scylladb.com
Technical documentationdrill.apache.org/­docsdocs.dolphindb.cn/­en/­help200/­index.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.scylladb.com
DeveloperApache Software FoundationDolphinDB, IncMicrosoftMicrosoftScyllaDB
Initial release20122018201020192015
Current release1.20.3, January 2023v2.00.4, January 2022cloud service with continuous releasesScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community version availableOpen Source infoMIT LicensecommercialOpen Source infoOpen Source (AGPL), commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageC++.NET and CC++
Server operating systemsLinux
OS X
Windows
Linux
Windows
.NEThostedLinux
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
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.nononoyesno
Secondary indexesnoyesall fields are automatically indexedyes infocluster global secondary indices
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like query languagenoKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements (CQL)
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
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
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
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
Server-side scripts infoStored proceduresuser defined functionsyesyesYes, possible languages: KQL, Python, Ryes, Lua
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
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.selectable replication factor infoRepresentation of geographical distribution of servers is possible
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
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonono infoAtomicity and isolation are supported for single operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 infoin-memory tables
User concepts infoAccess controlDepending on the underlying data sourceAdministrators, Users, GroupsAzure Active Directory AuthenticationAccess rights for users can be defined per object
More information provided by the system vendor
Apache DrillDolphinDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerScyllaDB
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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Apache DrillDolphinDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerScyllaDB
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