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DBMS > Google BigQuery vs. Heroic vs. Microsoft Azure Cosmos DB vs. Speedb

System Properties Comparison Google BigQuery vs. Heroic vs. Microsoft Azure Cosmos DB vs. Speedb

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSpeedb  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchGlobally distributed, horizontally scalable, multi-model database serviceAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB
Primary database modelRelational DBMSTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.26
Rank#310  Overall
#45  Key-value stores
Websitecloud.google.com/­bigquerygithub.com/­spotify/­heroicazure.microsoft.com/­services/­cosmos-dbwww.speedb.io
Technical documentationcloud.google.com/­bigquery/­docsspotify.github.io/­heroiclearn.microsoft.com/­azure/­cosmos-db
DeveloperGoogleSpotifyMicrosoftSpeedb
Initial release2010201420142020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedhostedLinux
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infoJSON typesno
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
Secondary indexesnoyes infovia Elasticsearchyes infoAll properties auto-indexed by defaultno
SQL infoSupport of SQLyesnoSQL-like query languageno
APIs and other access methodsRESTful HTTP/JSON APIHQL (Heroic Query Language, a JSON-based language)
HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnoJavaScriptno
TriggersnonoJavaScript
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoMulti-item ACID transactions with snapshot isolation within a partitionyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights can be defined down to the item levelno
More information provided by the system vendor
Google BigQueryHeroicMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSpeedb
Specific characteristicsSpeedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Licensing and pricing modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more

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More resources
Google BigQueryHeroicMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSpeedb
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