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DBMS > GeoSpock vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Vitess

System Properties Comparison GeoSpock vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Vitess

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonVitess  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsTime Series 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
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitegeospock.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorersqrrl.comvitess.io
Technical documentationwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorervitess.io/­docs
DeveloperGeoSpockMicrosoftMicrosoftAmazon infooriginally Sqrrl Data, Inc.The Linux Foundation, PlanetScale
Initial release2010201920122013
Current release2.0, September 2019cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, Javascript.NET and CJavaGo
Server operating systemshosted.NEThostedLinuxDocker
Linux
macOS
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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 indexestemporal, categoricalall fields are automatically indexedyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)noKusto Query Language (KQL), SQL subsetnoyes infowith proprietary extensions
APIs and other access methodsJDBCRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
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 proceduresnoyesYes, possible languages: KQL, Python, Rnoyes infoproprietary syntax
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of HadoopMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.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 datanononoAtomic updates per row, document, or graph entityACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per tableAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Users with fine-grained authorization concept infono user groups or roles

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More resources
GeoSpockGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerSqrrlVitess
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How GeoSpock is supercharging geospatial analytics
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nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
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AWS beefs up threat detection with Sqrrl acquisition
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PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
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