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DBMS > Google BigQuery vs. Microsoft Azure Table Storage vs. Stardog vs. YugabyteDB

System Properties Comparison Google BigQuery vs. Microsoft Azure Table Storage vs. Stardog vs. YugabyteDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonStardog  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA Wide Column Store for rapid development using massive semi-structured datasetsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationHigh-performance distributed SQL database for global, internet-scale applications. Wire compatible with PostgreSQL.
Primary database modelRelational DBMSWide column storeGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score37.63
Rank#24  Overall
#15  Relational DBMS
Score4.29
Rank#77  Overall
#5  Wide column stores
Score1.71
Rank#126  Overall
#10  Graph DBMS
#6  RDF stores
Score0.95
Rank#177  Overall
#89  Relational DBMS
Websitecloud.google.com/­bigqueryazure.microsoft.com/­en-us/­services/­storage/­tableswww.stardog.comwww.yugabyte.com
Technical documentationcloud.google.com/­bigquery/­docsdocs.stardog.comdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperGoogleMicrosoftStardog-UnionYugabyte Inc.
Initial release2010201220102017
Current release7.3.0, May 20202.4, January 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemshostedhostedLinux
macOS
Windows
Linux
OS X
Data schemeyesschema-freeschema-free and OWL/RDFS-schema supportdepending on used data model
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono infoImport/export of XML data possibleno
Secondary indexesnonoyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLyesnoYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes, PostgreSQL compatible
APIs and other access methodsRESTful HTTP/JSON APIRESTful HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnouser defined functions and aggregates, HTTP Server extensions in Javayes infosql, plpgsql, C
Triggersnonoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicenoneHash and Range Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication in HA-ClusterBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-ClusterStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataoptimistic lockingACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)Access rights based on private key authentication or shared access signaturesAccess rights for users and rolesyes
More information provided by the system vendor
Google BigQueryMicrosoft Azure Table StorageStardogYugabyteDB
Specific characteristicsStardog is an Enterprise Knowledge Graph platform, uniquely combining graph storage...
» more
Competitive advantagesStardog provides a full featureset to aid in data integration for your complex data....
» more
Typical application scenariosStardog is frequently used for: Anti-money laundering & fraud monitoring Customer...
» more
Key customersBosch, Dow Jones, Elsevier, Ericsson, Morgan Stanley, NASA, NIH, Nokia, Salesforce,...
» more
Market metricsStardog's technology is based on ground-breaking research by our founders cited 10,000+...
» more
Licensing and pricing modelsA fully-featured 60-day Trial license is available for those testing Stardog; contact...
» more

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More resources
Google BigQueryMicrosoft Azure Table StorageStardogYugabyteDB
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