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DBMS > AlaSQL vs. Firebase Realtime Database vs. GridDB vs. TimescaleDB vs. Vertica

System Properties Comparison AlaSQL vs. Firebase Realtime Database vs. GridDB vs. TimescaleDB vs. Vertica

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGridDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionJavaScript DBMS libraryCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Scalable in-memory time series database optimized for IoT and Big DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Relational DBMS
Document storeTime Series DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsKey-value store
Relational DBMS
Relational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitealasql.orgfirebase.google.com/­products/­realtime-databasegriddb.netwww.timescale.comwww.vertica.com
Technical documentationgithub.com/­AlaSQL/­alasqlfirebase.google.com/­docs/­databasedocs.griddb.netdocs.timescale.comvertica.com/­documentation
DeveloperAndrey Gershun & Mathias R. WulffGoogle infoacquired by Google 2014Toshiba CorporationTimescaleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20142012201320172005
Current release5.1, August 20222.15.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMIT-LicensecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC++CC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedLinuxLinux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyesyes infonumerical, string, blob, geometry, boolean, timestampnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nononoyesno
Secondary indexesnoyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.noSQL92, SQL-like TQL (Toshiba Query Language)yes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJavaScript APIAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaScriptJava
JavaScript
Objective-C
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'nouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesCallbacks are triggered when data changesyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, across time and space (hash partitioning) attributeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageyesACID at container levelACIDACID
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.yesyesnono
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess rights for users can be defined per databasefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AlaSQLFirebase Realtime DatabaseGridDBTimescaleDBVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
AlaSQLFirebase Realtime DatabaseGridDBTimescaleDBVertica infoOpenText™ Vertica™
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