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DBMS > AlaSQL vs. Apache Impala vs. Databricks vs. Drizzle vs. Firebase Realtime Database

System Properties Comparison AlaSQL vs. Apache Impala vs. Databricks vs. Drizzle vs. Firebase Realtime Database

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFirebase Realtime Database  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.
DescriptionJavaScript DBMS libraryAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.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.
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument store
Relational DBMS
Relational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Websitealasql.orgimpala.apache.orgwww.databricks.comfirebase.google.com/­products/­realtime-database
Technical documentationgithub.com/­AlaSQL/­alasqlimpala.apache.org/­impala-docs.htmldocs.databricks.comfirebase.google.com/­docs/­database
DeveloperAndrey Gershun & Mathias R. WulffApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksDrizzle project, originally started by Brian AkerGoogle infoacquired by Google 2014
Initial release20142013201320082012
Current release4.1.0, June 20227.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache Version 2commercialOpen Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC++C++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)LinuxhostedFreeBSD
Linux
OS X
hosted
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
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.nonoyesno
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL-like DML and DDL statementswith Databricks SQLyes infowith proprietary extensionsno
APIs and other access methodsJavaScript APIJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBCAndroid
iOS
JavaScript API
RESTful HTTP API
Supported programming languagesJavaScriptAll languages supporting JDBC/ODBCPython
R
Scala
C
C++
Java
PHP
Java
JavaScript
Objective-C
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnolimited functionality with using 'rules'
Triggersyesnono infohooks for callbacks inside the server can be used.Callbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenoACIDACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPyes, based on authentication and database rules
More information provided by the system vendor
AlaSQLApache ImpalaDatabricksDrizzleFirebase Realtime Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
AlaSQLApache ImpalaDatabricksDrizzleFirebase Realtime Database
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