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DBMS > BigObject vs. Google Cloud Datastore vs. Realm vs. YugabyteDB

System Properties Comparison BigObject vs. Google Cloud Datastore vs. Realm vs. YugabyteDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRealm  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument storeDocument storeRelational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score7.60
Rank#52  Overall
#9  Document stores
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitebigobject.iocloud.google.com/­datastorerealm.iowww.yugabyte.com
Technical documentationdocs.bigobject.iocloud.google.com/­datastore/­docsrealm.io/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperBigObject, Inc.GoogleRealm, acquired by MongoDB in May 2019Yugabyte Inc.
Initial release2015200820142017
Current release2.19, September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC and C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Data schemeyesschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)noyes, PostgreSQL compatible
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresLuausing Google App Engineno inforuns within the applications so server-side scripts are unnecessaryyes infosql, plpgsql, C
TriggersnoCallbacks using the Google Apps Engineyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosnoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes
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.yesnoyes infoIn-Memory realmno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesyes
More information provided by the system vendor
BigObjectGoogle Cloud DatastoreRealmYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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BigObjectGoogle Cloud DatastoreRealmYugabyteDB
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