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DBMS > Badger vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Qdrant

System Properties Comparison Badger vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Qdrant

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high-performance vector database with neural network or semantic-based matching
Primary database modelKey-value storeRelational DBMSDocument storeKey-value store
Wide column store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.28
Rank#167  Overall
#8  Vector DBMS
Websitegithub.com/­dgraph-io/­badgerwww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablegithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docsqdrant.tech/­documentation
DeveloperDGraph LabsEsgynGoogle infoacquired by Google 2014GoogleQdrant
Initial release20172015201220152021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaRust
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedhostedDocker
Linux
macOS
Windows
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesnoNumbers, Strings, Geo, Boolean
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.nonononono
Secondary indexesnoyesyesnoyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnoyesnonono
APIs and other access methodsADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesGoAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnoJava Stored Procedureslimited functionality with using 'rules'no
TriggersnonoCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency, tunable consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Key-based authentication

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More resources
BadgerEsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableQdrant
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