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Google BigQuery vs Realm React Native: What are the differences?
# Introduction
This Markdown code snippet provides a comparison between Google BigQuery and Realm React Native, highlighting key differences between the two.
1. **Data Storage**: Google BigQuery is a cloud-based data warehouse that allows for the storage of massive datasets and provides scalability. On the other hand, Realm React Native is a mobile database that stores data locally on the device for offline access.
2. **Query Language**: BigQuery utilizes SQL for querying data, which is a standard language that many developers are familiar with. In contrast, Realm React Native uses its own object-based query language, making it unique to work with compared to traditional SQL queries.
3. **Real-time Sync**: Realm React Native offers real-time data synchronization between the local database and server, enabling seamless updates across all device instances. Google BigQuery, on the other hand, does not provide real-time sync functionality out of the box.
4. **Platform Compatibility**: Google BigQuery is a cloud-based service accessible from various platforms and devices with an internet connection. Realm React Native, on the other hand, is specifically designed for mobile applications built with React Native as it integrates seamlessly with the framework.
5. **Cost Model**: Google BigQuery follows a pay-as-you-go pricing model based on the amount of data processed, making it scalable but potentially more expensive for larger datasets. Realm React Native, being a local database solution, does not incur ongoing costs related to data storage or data processing.
6. **Data Constraints**: Google BigQuery is optimized for handling large datasets, making it suitable for enterprise-level applications that require extensive data processing capabilities. In contrast, Realm React Native is more appropriate for smaller to medium-sized applications with data storage needs limited to the device's capacity.
In Summary, this Markdown code snippet highlights the key differences between Google BigQuery and Realm React Native, focusing on data storage, query language, real-time sync, platform compatibility, cost model, and data constraints.
Cloud Data-warehouse is the centerpiece of modern Data platform. The choice of the most suitable solution is therefore fundamental.
Our benchmark was conducted over BigQuery and Snowflake. These solutions seem to match our goals but they have very different approaches.
BigQuery is notably the only 100% serverless cloud data-warehouse, which requires absolutely NO maintenance: no re-clustering, no compression, no index optimization, no storage management, no performance management. Snowflake requires to set up (paid) reclustering processes, to manage the performance allocated to each profile, etc. We can also mention Redshift, which we have eliminated because this technology requires even more ops operation.
BigQuery can therefore be set up with almost zero cost of human resources. Its on-demand pricing is particularly adapted to small workloads. 0 cost when the solution is not used, only pay for the query you're running. But quickly the use of slots (with monthly or per-minute commitment) will drastically reduce the cost of use. We've reduced by 10 the cost of our nightly batches by using flex slots.
Finally, a major advantage of BigQuery is its almost perfect integration with Google Cloud Platform services: Cloud functions, Dataflow, Data Studio, etc.
BigQuery is still evolving very quickly. The next milestone, BigQuery Omni, will allow to run queries over data stored in an external Cloud platform (Amazon S3 for example). It will be a major breakthrough in the history of cloud data-warehouses. Omni will compensate a weakness of BigQuery: transferring data in near real time from S3 to BQ is not easy today. It was even simpler to implement via Snowflake's Snowpipe solution.
We also plan to use the Machine Learning features built into BigQuery to accelerate our deployment of Data-Science-based projects. An opportunity only offered by the BigQuery solution
Pros of Google BigQuery
- High Performance28
- Easy to use25
- Fully managed service22
- Cheap Pricing19
- Process hundreds of GB in seconds16
- Big Data12
- Full table scans in seconds, no indexes needed11
- Always on, no per-hour costs8
- Good combination with fluentd6
- Machine learning4
- Easy to manage1
- Easy to learn0
Pros of Realm React Native
- Reactive Database1
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Cons of Google BigQuery
- You can't unit test changes in BQ data1
- Sdas0
Cons of Realm React Native
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What is Google BigQuery?
What is Realm React Native?
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