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DBMS > Graph Engine vs. LevelDB vs. Microsoft Azure Data Explorer

System Properties Comparison Graph Engine vs. LevelDB vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesFully managed big data interactive analytics platform
Primary database modelGraph DBMS
Key-value store
Key-value storeRelational DBMS infocolumn oriented
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
Score0.64
Rank#241  Overall
#21  Graph DBMS
#35  Key-value stores
Score3.32
Rank#100  Overall
#16  Key-value stores
Score5.82
Rank#65  Overall
#37  Relational DBMS
Websitewww.graphengine.iogithub.com/­google/­leveldbazure.microsoft.com/­services/­data-explorer
Technical documentationwww.graphengine.io/­docs/­manualgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperMicrosoftGoogleMicrosoft
Initial release201020112019
Current release1.23, February 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CC++
Server operating systems.NETIllumos
Linux
OS X
Windows
hosted
Data schemeyesschema-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-types
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.nonoyes
Secondary indexesnoall fields are automatically indexed
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
F#
Visual Basic
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
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 datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 storageyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnoAzure Active Directory Authentication
More information provided by the system vendor
Graph Engine infoformer name: TrinityLevelDBMicrosoft Azure Data Explorer
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
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Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more
Licensing and pricing modelsAn Azure Data Explorer cluster is a pair of engine and data management clusters which...
» more

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Graph Engine infoformer name: TrinityLevelDBMicrosoft Azure Data Explorer
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