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DBMS > BoltDB vs. Drizzle vs. Firebase Realtime Database vs. Spark SQL

System Properties Comparison BoltDB vs. Drizzle vs. Firebase Realtime Database vs. Spark SQL

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDrizzle  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn embedded key-value store for Go.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score14.29
Rank#39  Overall
#6  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­boltdb/­boltfirebase.google.com/­products/­realtime-databasespark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerGoogle infoacquired by Google 2014Apache Software Foundation
Initial release2013200820122014
Current release7.2.4, September 20123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsnoSQL-like DML and DDL statements
APIs and other access methodsJDBCAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGoC
C++
Java
PHP
Java
JavaScript
Objective-C
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonolimited functionality with using 'rules'no
Triggersnono infohooks for callbacks inside the server can be used.Callbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDyesno
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.nono
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPyes, based on authentication and database rulesno

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More resources
BoltDBDrizzleFirebase Realtime DatabaseSpark SQL
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