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Amazon Redshift Spectrum vs Presto: What are the differences?
# Key Differences Between Amazon Redshift Spectrum and Presto
Amazon Redshift Spectrum and Presto are both powerful query engines that can run complex SQL queries on large datasets stored in different data sources. However, there are key differences between the two technologies that users should consider before choosing one over the other.
1. **Integration with Data Warehouse**: Amazon Redshift Spectrum is tightly integrated with Amazon Redshift data warehouse, allowing users to seamlessly query data stored in Amazon S3 as an extension of their Redshift cluster. In contrast, Presto is a standalone distributed SQL query engine that can connect to various data sources, including Hadoop, Cassandra, and relational databases.
2. **Cost Structure**: Redshift Spectrum charges users based on the amount of data scanned in Amazon S3 during query execution, while Presto is open-source software that can be deployed on any hardware, resulting in potentially lower costs, especially for large-scale workloads that involve frequent data scans. Users should consider their budget and usage patterns when deciding between the two technologies.
3. **Performance Optimization**: Redshift Spectrum leverages the columnar storage format of Amazon S3 for optimized query performance, but it may introduce additional latency due to data transfer between S3 and Redshift. On the other hand, Presto is designed for interactive query processing and can achieve low latency by utilizing in-memory processing and parallel query execution.
4. **Ease of Use**: Amazon Redshift Spectrum offers a simplified setup process for users already familiar with Amazon Redshift, as it can be enabled with a few clicks in the AWS Management Console. Presto, on the other hand, requires more manual configuration and tuning to achieve optimal performance, making it better suited for users with advanced technical skills and knowledge of distributed systems.
5. **Data Processing Capabilities**: Redshift Spectrum supports the use of familiar SQL syntax and business intelligence tools for querying data in S3, making it easier for users to transition from traditional data warehousing environments. Presto, being a general-purpose query engine, provides more flexibility in processing complex data types and formats, such as JSON, Avro, and Parquet, without the need for predefined schemas.
6. **Scalability and Concurrency**: Amazon Redshift Spectrum scales automatically based on the query velocity and data volume without the need for manual scaling adjustments by the user. In comparison, Presto allows users to customize the cluster configuration to meet specific performance requirements, enabling greater control over resource allocation and query concurrency for demanding workloads.
In Summary, Amazon Redshift Spectrum is a more integrated and cost-effective solution for users heavily invested in the AWS ecosystem looking for seamless data querying capabilities, while Presto offers more flexibility and customization options for users with diverse data processing needs and technical expertise outside of a specific cloud platform.
To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.
Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.
We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.
Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.
Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.
#BigData #AWS #DataScience #DataEngineering
The platform deals with time series data from sensors aggregated against things( event data that originates at periodic intervals). We use Cassandra as our distributed database to store time series data. Aggregated data insights from Cassandra is delivered as web API for consumption from other applications. Presto as a distributed sql querying engine, can provide a faster execution time provided the queries are tuned for proper distribution across the cluster. Another objective that we had was to combine Cassandra table data with other business data from RDBMS or other big data systems where presto through its connector architecture would have opened up a whole lot of options for us.
Pros of Amazon Redshift Spectrum
- Good Performance1
- Great Documentation1
- Economical1
Pros of Presto
- Works directly on files in s3 (no ETL)18
- Open-source13
- Join multiple databases12
- Scalable10
- Gets ready in minutes7
- MPP6
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What is Amazon Redshift Spectrum?
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