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DBMS > Microsoft Azure Table Storage vs. TinkerGraph vs. Vertica vs. XTDB

System Properties Comparison Microsoft Azure Table Storage vs. TinkerGraph vs. Vertica vs. XTDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonTinkerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsA 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.A general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelWide column storeGraph DBMSRelational DBMS infoColumn orientedDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.08
Rank#348  Overall
#35  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablestinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.vertica.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationvertica.com/­documentationwww.xtdb.com/­docs
DeveloperMicrosoftOpenText infopreviously Micro Focus and Hewlett PackardJuxt Ltd.
Initial release2012200920052019
Current release12.0.3, January 20231.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoLimited community edition freeOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Clojure
Server operating systemshostedLinuxAll OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
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.nononono
Secondary indexesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.limited SQL, making use of Apache Calcite
APIs and other access methodsRESTful HTTP APITinkerPop 3ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
HTTP REST
JDBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Clojure
Java
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnonoyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenonehorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
Durability infoSupport for making data persistentyesoptionalyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Microsoft Azure Table StorageTinkerGraphVertica infoOpenText™ Vertica™XTDB infoformerly named Crux
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Microsoft Azure Table StorageTinkerGraphVertica infoOpenText™ Vertica™XTDB infoformerly named Crux
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