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DBMS > AlaSQL vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Neo4j vs. Vertica

System Properties Comparison AlaSQL vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Neo4j vs. Vertica

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  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.Fully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsCloud 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 storeRelational DBMS infocolumn orientedGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitealasql.orgfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­data-explorerneo4j.comwww.vertica.com
Technical documentationgithub.com/­AlaSQL/­alasqlfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docsvertica.com/­documentation
DeveloperAndrey Gershun & Mathias R. WulffGoogle infoacquired by Google 2014MicrosoftNeo4j, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20142012201920072005
Current releasecloud service with continuous releases5.20, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMIT-LicensecommercialcommercialOpen Source infoGPL version3, commercial licenses availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJavaScriptJava, ScalaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedhostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalYes, 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 infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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 indexesnoyesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache LuceneNo 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.noKusto Query Language (KQL), SQL subsetnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJavaScript APIAndroid
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaScriptJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'Yes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesCallbacks are triggered when data changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handleryes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceyes using Neo4j Fabrichorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-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 methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono 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
Eventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageyesnoACIDACID
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 controlnoyes, based on authentication and database rulesAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AlaSQLFirebase Realtime DatabaseMicrosoft Azure Data ExplorerNeo4jVertica infoOpenText™ Vertica™
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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