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DBMS > Graph Engine vs. Microsoft Azure Data Explorer vs. QuestDB vs. Sqrrl vs. Warp 10

System Properties Comparison Graph Engine vs. Microsoft Azure Data Explorer vs. QuestDB vs. Sqrrl vs. Warp 10

Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuestDB  Xexclude from comparisonSqrrl  Xexclude from comparisonWarp 10  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformA high performance open source SQL database for time series dataAdaptable, secure NoSQL built on Apache AccumuloTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelGraph DBMS
Key-value store
Relational DBMS infocolumn orientedTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Time Series 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.graphengine.ioazure.microsoft.com/­services/­data-explorerquestdb.iosqrrl.comwww.warp10.io
Technical documentationwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerquestdb.io/­docswww.warp10.io/­content/­02_Getting_started
DeveloperMicrosoftMicrosoftQuestDB Technology IncAmazon infooriginally Sqrrl Data, Inc.SenX
Initial release20102019201420122015
Current releasecloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0commercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CJava (Zero-GC), C++, RustJavaJava
Server operating systems.NEThostedLinux
macOS
Windows
LinuxLinux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes infoschema-free via InfluxDB Line Protocolschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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.noyesnono
Secondary indexesall fields are automatically indexednoyesno
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL with time-series extensionsnono
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
HTTP API
Jupyter
WebSocket
Supported programming languagesC#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnonoyes infoWarpScript
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)Sharding infomaking use of HadoopSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with eventual consistencyselectable replication factor infomaking use of Hadoopselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID for single-table writesAtomic updates per row, document, or graph entityno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infothrough memory mapped filesyes
User concepts infoAccess controlAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Mandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
Graph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerQuestDBSqrrlWarp 10
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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More resources
Graph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerQuestDBSqrrlWarp 10
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