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DBMS > Amazon DocumentDB vs. Datomic vs. Firebase Realtime Database vs. Oracle Berkeley DB vs. VelocityDB

System Properties Comparison Amazon DocumentDB vs. Datomic vs. Firebase Realtime Database vs. Oracle Berkeley DB vs. VelocityDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatomic  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Widely used in-process key-value storeA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelDocument storeRelational DBMSDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Graph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websiteaws.amazon.com/­documentdbwww.datomic.comfirebase.google.com/­products/­realtime-databasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlvelocitydb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datomic.comfirebase.google.com/­docs/­databasedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlvelocitydb.com/­UserGuide
DeveloperCognitectGoogle infoacquired by Google 2014Oracle infooriginally developed by Sleepycat, which was acquired by OracleVelocityDB Inc
Initial release20192012201219942011
Current release1.0.6735, June 202318.1.40, May 20207.x
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source infocommercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC, Java, C++ (depending on the Berkeley DB edition)C#
Server operating systemshostedAll OS with a Java VMhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Any that supports .NET
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nononoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnononoyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIAndroid
iOS
JavaScript API
RESTful HTTP API
.Net
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
Java
Java
JavaScript
Objective-C
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
Server-side scripts infoStored proceduresnoyes infoTransaction Functionslimited functionality with using 'rules'nono
TriggersnoBy using transaction functionsCallbacks are triggered when data changesyes infoonly for the SQL APICallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnone infoBut extensive use of caching in the application peersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlAccess rights for users and rolesnoyes, based on authentication and database rulesnoBased on Windows Authentication

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More resources
Amazon DocumentDBDatomicFirebase Realtime DatabaseOracle Berkeley DBVelocityDB
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