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DBMS > Ingres vs. Microsoft Azure Data Explorer vs. STSdb vs. TinkerGraph vs. Vertica

System Properties Comparison Ingres vs. Microsoft Azure Data Explorer vs. STSdb vs. TinkerGraph vs. Vertica

Editorial information provided by DB-Engines
NameIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparisonTinkerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionWell established RDBMSFully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APICloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedKey-value storeGraph DBMSRelational 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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.08
Rank#348  Overall
#35  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4tinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.vertica.com
Technical documentationdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperActian CorporationMicrosoftSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release1974 infooriginally developed at University Berkely in early 1970s2019201120092005
Current release11.2, May 2022cloud service with continuous releases4.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPLv2, commercial license availableOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC#JavaC++
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedWindowsLinux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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-typesyes infoprimitive types and user defined types (classes)yesyes
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.no infobut tools for importing/exporting data from/to XML-files availableyesnono
Secondary indexesyesall fields are automatically indexednonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client APITinkerPop 3ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
Groovy
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud servicenonenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
noneImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayes infoMVCCyesyesnoyes
Durability infoSupport for making data persistentyesyesyesoptionalyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
IngresMicrosoft Azure Data ExplorerSTSdbTinkerGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
IngresMicrosoft Azure Data ExplorerSTSdbTinkerGraphVertica infoOpenText™ Vertica™
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