#firestore

FOR IMMEDIATE RELEASE SEOSiri, a leader in digital strategy and data-driven growth systems, has officially released FireRule Guard for the Visual Studio Code Marketplace. As digital infrastructures move toward total automation, the “Security Debt” created by manual database configuration has become a critical vulnerability for e-commerce sites and software-as-a-service (SaaS) providers.…

With asynchronous variables recently released in server-side Google Tag Manager, it’s time to dig into data enrichment flows using another release from the Google team. * drum roll * We have a new Google Cloud Platform API! It’s fast. It’s sleek. It’s beautiful. It’s Firestore! Firestore is a NoSQL, transactional, and scalable database that offers near-real-time write/read and sync operations for…

Google Cloudデータベース比較 Google Cloudデータベース比較 Google Cloudデータベースサービスの概要と重要性 皆様、こんにちは。株式会社 十志（JUICY）のペルソナAI、JUICYと申します。今回は、クラウドサービスの巨人、Google Cloudが提供するデータベースサービスに焦点を当て、その詳細を深く掘り下げてまいります。 IT導入や活用に関心を持つ中小企業の皆様にとって、事業活動を支えるデータの管理は非常に重要です。データベースは、事業の継続性を担保し、成長を支える基盤となります。Google…

Google Cloud Databases

The folks at Loyal Guru are aware of the difficulties merchants have in fostering consumer engagement and loyalty in the face of quickly changing consumer demands. Retail clients can use Loyal Guru’s loyalty and offer personalization platform to analyse customer data and dynamically customise promotions to match specific contexts and preferences. The objective is to assist shops in building enduring relationships by making them more relevant.

Innovation is essential to us because the retail industry is constantly changing and neither should they. Loyal Guru was aware that a strong platform will enable the rapid and large-scale delivery of fully personalised experiences. For the purpose of managing Loyal Guru’s databases and infrastructure, Loyal Guru teamed with Google Cloud. AlloyDB offers the performance and agility required to continuously improve the features of Loyal Guru’s platform and assist us in seeing new patterns rather than just responding to them. These technologies work well along with other Google  Cloud databases offerings like Firestore and BigQuery.

Enabling customisation with high-performance database systems

With customised offers, promotions, and brand experiences, merchants can connect customers on a deep level with the aid of Loyal Guru. However, sophisticated data processing and analytics capabilities are needed to deliver this at scale. Retailers who want to achieve precise audience segmentation and dynamic offer changes that maximise relevance must absorb and act upon customers’ behavioural data in real time across various touchpoints.

These vital personalisation features require a scalable, high-performance database to power. Customers of Loyal Guru want immediate access to transactional records, offer specifics, customer data, and more for updating and querying during customer interactions. Database overload causes sluggish replies and unsatisfactory client experiences. For this reason, Loyal Guru decided to use Google  Cloud databases as the foundation for their platform.

A scalable, safe database approach

Firestore, BigQuery, and AlloyDB for PostgreSQL are the three potent Google  Cloud databases technologies at the centre of Loyal Guru’s architecture.

Transactional workloads using AlloyDB

Loyal Guru’s relational database, AlloyDB, provides better performance and faster analytical capabilities than they had anticipated. Loyal Guru was aware that Google Cloud databases offer remarkable scalability and speed. AlloyDB powers all of Loyal Guru’s essential transactional functions, such as offer redemptions, user profiles, and loyalty programme details. It guarantees dependable, latency-free access to this vital data for Loyal Guru APIs. It also offers a solid platform on which to begin leveraging the capabilities of Gemini and AlloyDB to develop generative AI applications that will enable Loyal Guru to offer more services.

Large traffic surges from significant shopping events on Loyal Guru frequently resulted in bottlenecks prior to the use of AlloyDB. The proliferation of data was difficult for Loyal Guru to handle, pushing the boundaries of their storage capacity. These problems have been significantly reduced by AlloyDB’s autopilot storage management feature, which automatically modifies store capacity to satisfy Loyal Guru demands without the need for human involvement. In total, Loyal Guru optimised storage from 2TB to 1.3TB, a 35% improvement, and decreased query latency by 40–50%.

Firestore for reads with a high concurrency

For high-throughput read operations on comparatively static data, such loyalty point balances and product catalogues, Loyal Guru uses Firestore in Datastore Mode. Its capacity to manage high concurrency without sacrificing speed makes it perfect for workloads that require a lot of reading. Because of this, Loyal Guru’s platform was able to continue operating with great availability and performance even when stores utilising its services sent in the highest read loads.

BigQuery for data analysis

Loyal Guru processes massive behavioural datasets through BigQuery for analytics and business intelligence in order to maximise the value from its data assets. As the data warehouse solution for Loyal Guru, Loyal Guru uses BigQuery to execute intricate queries, show patterns, and provide insights that inform strategic choices. Based on the data of Loyal Guru customers, these analytics capabilities are essential for optimising marketing tactics, product roadmaps, and Loyal Guru personalization models. Their ability to process large datasets and intricate queries quickly is further enhanced by BigQuery’s scalable and fully managed architecture, which keeps us free from infrastructure bottlenecks.

To assist us deliver a safe service with high availability, Loyal Guru uses a number of Google  Cloud databases components in addition to these three data products. We can scale Loyal Guru APIs automatically thanks to Google App Engine’s flexible environment, and Loyal Guru uses Firebase Hosting to host their progressive web app (PWA) for campaign management. For cloud-native security and traffic distribution, Loyal Guru also uses  Cloud Armour and Cloud Load Balancing.

Loyal Guru may increase the scalability and dependability of their services through cloud balancing by enhancing rotation and escalation procedures. In addition, Loyal Guru can screen outgoing or invalid attacks before they reach the GAE Service. This works in tandem with Cloud Armour, enabling us to identify certain attack attempts such as XSS, SQLi, and other prevalent malevolent activities.

Loyal Guru is still using Google Cloud

Loyal Guru has enhanced security, raised database speed, and met Loyal Guru SLA promises to their clients by optimising their infrastructure with Google Cloud’s completely managed services. Their Loyal Guru APIs now have roughly 60% less latency when connecting to Google  Cloud databases.

Loyal Guru intends to use read replicas in the future for improved availability and dependability. Additionally, Loyal Guru wants to take use of AlloyDB’s impending horizontal scalability features to facilitate future growth. To get closer to real-time operational procedures, Loyal Guru also intends to shift a portion of its BigQuery workloads to AlloyDB.

Google  Cloud Database

For Loyal Guru, Google Cloud’s robust database services have changed the game by enabling us to reliably and scalable provide shops with relevant content. These Google Cloud databases will be essential for fostering innovation and exceeding client expectations as Loyal Guru keeps pushing the envelope.

import grpc import firestore from google.cloud.firestore_v1.services.firestore import client as firestore_client from google.cloud.firestore_v1.services.firestore.transports.grpc import FirestoreGrpcTransport channel = grpc.insecure_channel("localhost:8080") transport = FirestoreGrpcTransport(channel=channel) firestore_db = firestore.Client() firestore_db._firestore_api_internal =…