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DBMS > AlaSQL vs. Apache Impala vs. Drizzle vs. Firebase Realtime Database vs. Google Cloud Datastore

System Properties Comparison AlaSQL vs. Apache Impala vs. Drizzle vs. Firebase Realtime Database vs. Google Cloud Datastore

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  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 HadoopMySQL 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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSDocument storeDocument 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
Score14.29
Rank#39  Overall
#6  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Websitealasql.orgimpala.apache.orgfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastore
Technical documentationgithub.com/­AlaSQL/­alasqlimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docs
DeveloperAndrey Gershun & Mathias R. WulffApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerGoogle infoacquired by Google 2014Google
Initial release20142013200820122008
Current release4.1.0, June 20227.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache Version 2Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC++C++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)LinuxFreeBSD
Linux
OS X
hostedhosted
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyesyes, details here
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.nononono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL-like DML and DDL statementsyes infowith proprietary extensionsnoSQL-like query language (GQL)
APIs and other access methodsJavaScript APIJDBC
ODBC
JDBCAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesJavaScriptAll languages supporting JDBC/ODBCC
C++
Java
PHP
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenolimited functionality with using 'rules'using Google App Engine
Triggersyesnono infohooks for callbacks inside the server can be used.Callbacks are triggered when data changesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyesnoyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenoACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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 rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
AlaSQLApache ImpalaDrizzleFirebase Realtime DatabaseGoogle Cloud Datastore
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