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DBMS > Databend vs. Firebase Realtime Database vs. Hive vs. TimescaleDB

System Properties Comparison Databend vs. Firebase Realtime Database vs. Hive vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHive  Xexclude from comparisonTimescaleDB  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 complexityCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.data warehouse software for querying and managing large distributed datasets, built on HadoopA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
firebase.google.com/­products/­realtime-databasehive.apache.orgwww.timescale.com
Technical documentationdocs.databend.comfirebase.google.com/­docs/­databasecwiki.apache.org/­confluence/­display/­Hive/­Homedocs.timescale.com
DeveloperDatabend LabsGoogle infoacquired by Google 2014Apache Software Foundation infoinitially developed by FacebookTimescale
Initial release2021201220122017
Current release1.0.59, April 20233.1.3, April 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustJavaC
Server operating systemshosted
Linux
macOS
hostedAll OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Java
JavaScript
Objective-C
C++
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yes infouser defined functions and integration of map-reduceuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersnoCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesnoACID
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.no
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesyes, based on authentication and database rulesAccess rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
DatabendFirebase Realtime DatabaseHiveTimescaleDB
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