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Google Cloud Bigtable VS Redis

Compare Google Cloud Bigtable VS Redis and see what are their differences

Google Cloud Bigtable logo Google Cloud Bigtable

A high performance NoSQL database service for large analytical and operational workloads.

Redis logo Redis

Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
  • Google Cloud Bigtable Landing page
    Landing page //
    2023-09-12
  • Redis Landing page
    Landing page //
    2022-10-19

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

Google Cloud Bigtable features and specs

  • Scalability
    Google Cloud Bigtable is designed to scale horizontally to handle massive amounts of data across millions of rows and thousands of columns. This makes it ideal for applications needing to handle large datasets with high throughput.
  • Low Latency
    Bigtable is optimized for low-latency access to big data. It is capable of delivering real-time responses, which is beneficial for applications that require fast read and write operations.
  • Seamless Integration
    Bigtable integrates easily with other GCP services like Google Cloud Storage, BigQuery, and Dataflow, simplifying the development of complex applications that require various cloud services.
  • Managed Service
    As a managed service, Bigtable handles routine operations such as scaling, replication, and failure recovery, allowing users to focus on application development rather than infrastructure management.
  • Strong Consistency
    Bigtable provides strong consistency for read and write operations, ensuring that data is reliable and consistent across operations and query results.

Possible disadvantages of Google Cloud Bigtable

  • Complexity of Use
    Bigtable can be complex to set up and use effectively, especially for those who are unfamiliar with NoSQL databases or distributed systems.
  • Cost
    While scalable, the pricing can become expensive as your requirements grow, especially if you need high throughput and large storage capacities.
  • Limited Querying Capabilities
    Unlike relational databases, Bigtable has limited querying capabilities. It does not support SQL-like queries, making it less suitable for applications that require complex querying options.
  • Region-Specific Availability
    Bigtable is available only in certain regions, which might limit its use for global applications requiring multi-region deployments for latency optimization.
  • Learning Curve
    There's a significant learning curve for new users to understand Bigtable's architecture and its best practices, which can delay the development process.

Redis features and specs

  • Performance
    Redis is an in-memory data store, which allows it to provide extremely fast read and write operations. This makes it ideal for applications requiring real-time interactions.
  • Data Structures
    Redis offers a variety of data structures, such as strings, hashes, lists, sets, and sorted sets. This flexibility helps developers manage data more efficiently in different scenarios.
  • Scalability
    Redis supports horizontal scalability with features like clustering and partitioning, allowing for easy scaling as your application grows.
  • Persistence
    Though primarily an in-memory store, Redis provides options for data persistence, such as RDB snapshots and AOF logs, enabling data durability across reboots.
  • Pub/Sub Messaging
    Redis includes a built-in publish/subscribe messaging system, which can be used to implement real-time messaging and notifications.
  • Simple API
    Redis has a simple and intuitive API, which can speed up development time and make it easier to integrate Redis into various application stacks.
  • Atomic Operations
    Redis supports atomic operations on data structures, reducing the complexity of concurrent programming and making it easier to maintain data consistency.

Possible disadvantages of Redis

  • Memory Usage
    Being an in-memory data store, Redis can become expensive in terms of memory usage, especially when working with large datasets.
  • Data Persistence Limitations
    While Redis offers data persistence, it is not as robust as traditional databases. There can be data loss in certain configurations, such as when using asynchronous persistence methods.
  • Complexity in Scaling
    Although Redis supports clustering, setting up and managing a Redis cluster can be complex and may require significant DevOps expertise.
  • Single-threaded Nature
    Redis operates on a single-threaded event loop, which can become a bottleneck for certain workloads that could benefit from multi-threading.
  • Limited Query Capabilities
    Compared to traditional relational databases, Redis offers limited querying capabilities. Complex queries and joins are not supported natively.
  • License
    As of Redis 6 and higher, the Redis modules are under the Server Side Public License (SSPL), which may be restrictive for some use cases compared to more permissive open-source licenses.

Google Cloud Bigtable videos

Scalability Meetup @ Whitepages - Google Cloud BigTable

Redis videos

What is Redis? | Why and When to use Redis? | Tech Primers

More videos:

  • Review - Improve your Redis developer experience with RedisInsight, Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Category Popularity

0-100% (relative to Google Cloud Bigtable and Redis)
Databases
4 4%
96% 96
NoSQL Databases
3 3%
97% 97
Relational Databases
100 100%
0% 0
Key-Value Database
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Cloud Bigtable and Redis

Google Cloud Bigtable Reviews

7 Best NoSQL APIs
When businesses need to scale, they want to do so with limited downtime. The Google Cloud Bigtable provides horizontal Scaling in a matter of seconds without any downtime. To scale, cluster nodes are quickly added to increase your overall Bigtable cluster. Google even provides the option of scaling out only for a matter of hours, to handle a large load of requests. Once the...

Redis Reviews

Redis Alternative for App Performance | Gigaspaces
Redis offers a RESTful API for accessing data stored within its in-memory technology data structures. This API provides a simple and efficient way to interact with Redis, enabling developers to leverage its capabilities seamlessly in their applications. Developers also need to manage the Redis cached data lifecycle, it’s the application responsibility to store the data &...
Are Free, Open-Source Message Queues Right For You?
A notable challenge with Redis Streams is that it doesn't natively support distributed, horizontal scaling. Also, while Redis is famous for its speed and simplicity, managing and scaling a Redis installation may be complex for some users, particularly for persistent data workloads.
Source: blog.iron.io
Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
1. Redis: I'll start with Redis which I'd like to call the "original" key/value store (after memcached) because it is the oldest and most widely used of all. Being a long-time follower of Redis, I do know it's single-threaded (and uses io-threads since 6.0) and hence it achieves lesser throughput than the other stores listed above which are multi-threaded, at least to some...
Memcached vs Redis - More Different Than You Would Expect
Remember when I wrote about how Redis was using malloc to assign memory? I lied. While Redis did use malloc at some point, these days Redis actually uses jemalloc. The reason for this is that jemalloc, while having lower peak performance has lower memory fragmentation helping to solve the framented memory issues that Redis experiences.
Top 15 Kafka Alternatives Popular In 2021
Redis is a known, open-source, in-memory data structure store that offers different data structures like lists, strings, hashes, sets, bitmaps, streams, geospatial indexes, etc. It is best utilized as a cache, memory broker, and cache. It has optional durability and inbuilt replication potential. It offers a great deal of availability through Redis Sentinel and Redis Cluster.

Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than Google Cloud Bigtable. While we know about 218 links to Redis, we've tracked only 6 mentions of Google Cloud Bigtable. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google Cloud Bigtable mentions (6)

  • Vaultree and AlloyDB: the world's first Fully Homomorphic and Searchable Cloud Encryption Solution
    In my opinion, Google has built some fantastic database services like Bigtable and Spanner, which literally changed the industry for good, and I am eager to see how they will build upon this new service. With AlloyDB's disaggregated architecture, the dystopian world where I only pay for SQL databases per query and the stored data on GCP seems closer than ever. - Source: dev.to / over 2 years ago
  • Google Cloud Reference
    Cloud Bigtable: Petabyte-scale, low-latency, non-relational 🔗Link 🔗Link. - Source: dev.to / over 2 years ago
  • A Graph-Based Firebase
    > These triples say that the Layer with id 1 has a fontSize 20 and backgroundColor blue. Since they are different rows, there’s no conflict. This sounds a lot like Bigtable (https://cloud.google.com/bigtable), which also does last-write-wins conflict resolution layer. So this is adding a GraphQL + frontend layer to it? - Source: Hacker News / almost 3 years ago
  • The 4 Types of NoSQL Databases You Need to Know
    Google's BigTable paper inspired this database design, and it is capable of handling large data loads on distributed machines. In addition, column-oriented databases provide efficient compression and high performance with aggregated queries such as sum, average, and minimum. - Source: dev.to / almost 3 years ago
  • Can someone help me understand why data batch processing and data streaming processing pose such different challenges in data management?
    Because of these and other differences, the tools used are also different. With batch processing, data might be read from large files, processed, and stored in an OLTP (Online Transaction Processing) database (like MySQL) or OLAP (Online Analytical Processing) system (like Google BigQuery). But these would not be good solutions for streaming applications, because they are not optimized for high throughput on a lot... Source: over 3 years ago
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Redis mentions (218)

  • Cache Invalidation: The Silent Performance Killer
    Picture this: you've just built a snappy web app, and you're feeling pretty good about it. You've added Redis to cache frequently accessed data, and your app is flying—pages load in milliseconds, users are happy, and you're a rockstar. But then, a user updates their profile, and… oops. The app still shows their old info. Or worse, a new blog post doesn't appear on the homepage. What's going on? Welcome to the... - Source: dev.to / 7 days ago
  • Feature Comparison: Reliable Queue vs. Valkey and Redis Stream
    Valkey and Redis streams are data structures that act like append-only logs with some added features. Redisson PRO, the Valkey and Redis client for Java developers, improves on this concept with its Reliable Queue feature. - Source: dev.to / 13 days ago
  • Finding Bigfoot with Async Generators + TypeScript
    Of course, these examples are just toys. A more proper use for asynchronous generators is handling things like reading files, accessing network services, and calling slow running things like AI models. So, I'm going to use an asynchronous generator to access a networked service. That service is Redis and we'll be using Node Redis and Redis Query Engine to find Bigfoot. - Source: dev.to / 27 days ago
  • Caching Isn’t Always the Answer – And Here’s Why
    Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / 27 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Real-time serving: Many push processed data into low-latency serving layers like Redis to power applications needing instant responses (think fraud detection, live recommendations, financial dashboards). - Source: dev.to / about 1 month ago
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What are some alternatives?

When comparing Google Cloud Bigtable and Redis, you can also consider the following products

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Amazon Aurora - MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

Google Cloud Spanner - Google Cloud Spanner is a horizontally scalable, globally consistent, relational database service.