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DBMS > Databend vs. Google Cloud Spanner vs. ObjectBox

System Properties Comparison Databend vs. Google Cloud Spanner vs. ObjectBox

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Extremely fast embedded database for small devices, IoT and Mobile
Primary database modelRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­spannerobjectbox.io
Technical documentationdocs.databend.comcloud.google.com/­spanner/­docsdocs.objectbox.io
DeveloperDatabend LabsGoogleObjectBox Limited
Initial release202120172017
Current release1.0.59, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustC and C++
Server operating systemshosted
Linux
macOS
hostedAndroid
iOS
Linux
macOS
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary native API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Go
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication with 3 replicas for regional instances.online/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
DatabendGoogle Cloud SpannerObjectBox
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