DBMS > AlaSQL vs. Firebase Realtime Database vs. GraphDB vs. Microsoft Azure Data Explorer vs. SingleStore
System Properties Comparison AlaSQL vs. Firebase Realtime Database vs. GraphDB vs. Microsoft Azure Data Explorer vs. SingleStore
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | AlaSQL Xexclude from comparison | Firebase Realtime Database Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | JavaScript DBMS library | Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data. | Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL. | Fully managed big data interactive analytics platform | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Relational DBMS | Document store | Graph DBMS RDF store | Relational DBMS column oriented | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store If 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 this 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 support 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 see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Website | alasql.org | firebase.google.com/products/realtime-database | www.ontotext.com | azure.microsoft.com/services/data-explorer | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | github.com/AlaSQL/alasql | firebase.google.com/docs/database | graphdb.ontotext.com/documentation | docs.microsoft.com/en-us/azure/data-explorer | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Social network pages | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Andrey Gershun & Mathias R. Wulff | Google acquired by Google 2014 | Ontotext | Microsoft | SingleStore Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2014 | 2012 | 2000 | 2019 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 10.4, October 2023 | cloud service with continuous releases | 8.5, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source MIT-License | commercial | commercial Some plugins of GraphDB Workbench are open sourced | commercial | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | JavaScript | Java | C++, Go | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | server-less, requires a JavaScript environment (browser, Node.js) | hosted | All OS with a Java VM Linux OS X Windows | hosted | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | schema-free and OWL/RDFS-schema support; RDF shapes | Fixed schema with schema-less datatypes (dynamic) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | no | yes | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | all fields are automatically indexed | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Close to SQL99, but no user access control, stored procedures and host language bindings. | no | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | Kusto Query Language (KQL), SQL subset | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JavaScript API | Android iOS JavaScript API RESTful HTTP API | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | JavaScript | Java JavaScript Objective-C | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | limited functionality with using 'rules' | well-defined plugin interfaces; JavaScript server-side extensibility | Yes, possible languages: KQL, Python, R | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | Callbacks are triggered when data changes | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | none | Sharding Implicit feature of the cloud service | Sharding hash partitioning | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | none | Multi-source replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication stores two copies of each physical data partition on two separate nodes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | none | Eventual Consistency if the client is offline Immediate Consistency if the client is online | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Eventual Consistency Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | yes Constraint checking | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | yes only for local storage and DOM-storage | yes | ACID | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes by using IndexedDB, SQL.JS or proprietary FileStorage | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | no | yes, based on authentication and database rules | Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on. | Azure Active Directory Authentication | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
AlaSQL | Firebase Realtime Database | GraphDB former name: OWLIM | Microsoft Azure Data Explorer | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | Customers in various industries worldwide including US and International Industry... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | F ree Tier and Enterprise Edition » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Understanding the Graph Center of Excellence Migrating From LPG to RDF Graph Model Case study: Policy Enforcement Automation With Semantics Okay, RAG… We Have a Problem Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and servicesWe invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
AlaSQL | Firebase Realtime Database | GraphDB former name: OWLIM | Microsoft Azure Data Explorer | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems Create a Marvel Database with SQL and Javascript, the easy way Multi faceted data exploration in the browser using Leaflet and amCharts provided by Google News Realtime vs Cloud Firestore: Which Firebase Database to go? Atos cybersecurity blog: Misconfigured Firebase: A real-time cyber threat Don't be like these 900+ websites and expose millions of passwords via Firebase Google Firebase may have exposed 125M records from misconfigurations Google launches Firebase Genkit, a new open source framework for building AI-powered apps provided by Google News Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace Ontotext Unveils GraphDB 10.4 with Enhanced AWS Integration and ChatGPT Connector Ontotext GraphDB is available on Azure, delivers rich knowledge graph experience Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released Ontotext's GraphDB 10 Brings Modern Data Architectures to the Mainstream with Better Resilience and Еаsier Operations provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services Log and Telemetry Analytics Performance Benchmark provided by Google News SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files Announcing watsonx.ai and SingleStore for generative AI applications provided by Google News |
Share this page