List of Google Cloud Memorystore Customers
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Since 2010, our global team of researchers has been studying Google Cloud Memorystore customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Google Cloud Memorystore for Database Management from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Google Cloud Memorystore for Database Management include: Gojek, a Indonesia based Media organisation with 24600 employees and revenues of $22.00 billion, Replit, a United States based Professional Services organisation with 150 employees and revenues of $20.0 million, Kyber Network, a British Virgin Islands based Banking and Financial Services organisation with 100 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using Google Cloud Memorystore, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Google Cloud Memorystore customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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Gojek | Media | 24600 | $22.0B | Indonesia | Google Cloud Memorystore | Database Management | 2018 | n/a | In 2018, Gojek deployed Google Cloud Memorystore as a low latency Redis cache inside its feature serving platform. Google Cloud Memorystore in the Database Management category was provisioned to support real time machine learning feature lookups used for operational decisioning. The implementation configured Google Cloud Memorystore for Redis to serve feature reads and to accept very high write throughput, supporting hundreds of thousands of updates per second. Configuration focused on in memory caching, shardable keyspace designs and eviction strategies typical for Redis to maintain subsecond access for feature retrieval. Google Cloud Memorystore was integrated into Gojek's real time ML pipelines for driver allocation, demand forecasting, dynamic pricing and personalization, providing a consistent feature store layer for downstream decision services. The deployment was supported by Google Cloud Professional Services and operated across Indonesia to meet peak dispatch and customer interaction demand. The rollout concentrated governance on operational monitoring, cluster sizing and availability to uphold tight SLAs for driver and customer interactions. The implementation improved latency and scalability for feature lookups and explicitly supported the stated throughput targets for Gojek's ML driven allocation and pricing functions. | ||
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Kyber Network | Banking and Financial Services | 100 | $10M | British Virgin Islands | Google Cloud Memorystore | Database Management | 2021 | n/a | In 2021, Kyber Network deployed Google Cloud Memorystore in a Database Management role to provide an in-memory Redis caching tier for its KyberSwap aggregator. The Memorystore deployment in Singapore caches real-time token price points and historic pricing, feeding AI algorithms that compute optimal trading routes for the trading aggregator. This implementation supports finance and trading operational workflows and was positioned to address read latency for price and routing decisions. Google Cloud Memorystore for Redis was configured as the primary fast read store for tick data and price snapshots, with short lived time to live policies and targeted cache invalidation to maintain pricing freshness. The caching layer serves model inference pipelines and the routing engine, reducing read contention and offloading persistent stores. Standard in-memory cache capabilities were leveraged to provide subsecond reads and atomic update patterns required by high frequency routing logic. Operationally the Memorystore instances were colocated with compute in the Singapore region to minimize network latency between the AI inference services and the caching tier. Integrations included the KyberSwap aggregator trading engine and internal AI routing services, with the cache exposed via the Redis protocol for synchronous reads during route computation. The scope covered production trading flows and peak traffic handling across Kyber Network trading features. Governance adjustments included establishing cache invalidation cadence and model refresh workflows to align the AI models with cached historic pricing. The move to Google Cloud Memorystore reduced trading latency from approximately 2 seconds to under 1 second, improved platform resilience during traffic spikes, and enabled faster time to market for new trading features. Google Cloud Memorystore is named in the implementation and the Database Management role is central to the described architecture. | ||
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Replit | Professional Services | 150 | $20M | United States | Google Cloud Memorystore | Database Management | 2017 | n/a | In 2017, Replit implemented Google Cloud Memorystore as a scalable, low-latency Redis backend. Replit used Google Cloud Memorystore, a Database Management service, to support its collaborative cloud IDE and execution environment for developers and classrooms across the United States. The deployment relied on the managed Redis offering to provide in-memory caching and session state for real-time editing, code execution orchestration, and ephemeral container coordination. Functional emphasis included low-latency key value operations, horizontal scaling of Redis instances, and managed service operational features such as automated maintenance and availability management. Adoption of Google Cloud Memorystore reduced the operational overhead of running self-managed Redis clusters and supported the platform scaling to millions of users and thousands of concurrent containers, preserving performance for Replit’s developer and education use cases. The implementation positioned Google Cloud Memorystore as a central Database Management component for Replit platform engineering, runtime operations, and inter-container coordination. |
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