Minimum of 10 megabytes per query execution.Price is per terabyte of data scanned during a query execution.Predictable price with no penalty on excess queries, but can increase overall cost with fixed compute (SSD) and storage (HDD).Hourly rate for both dense compute nodes and dense storage nodes.Based on type and number of nodes in a cluster.Converting data to columnar formats also helps with faster queries.Partitioning tables helps with faster queries and performance.Loading can be time consuming, but once loaded, queries are faster than Athena.Must request higher limits for any restriction.Strictly tied to S3 and operates as a managed system on top of data, therefore:.Strictly node based, making upgrading simple: scale up a cluster by adding nodes.Can easily query encrypted data stored in S3 and write encrypted results back to your S3 bucket.Users must have permission to access the the S3 data locations.Uses Amazon’s Identity Access Management (IAM).Various encryption methods can be applied to protect clusters, connections, and data files.Can use Amazon’s Virtual Private Cloud to protect access to your cluster.A cluster security group is needed to give other users access to clusters.Join Query – Slower than Redshift due to simpler focus.Aggregated – Slightly faster than Redshift.Built for running queries on a single data source, regardless of data organization.Copied files may reside in an S3 bucket, an EMR cluster, or on a remote host accessed Must use `COPY` command to move data into a table from data files or Amazon DynamoDB tables.Join Query – Faster than Athena due to the ability to easily handle traditional joins and relational workloads.Aggregated – Slightly slower than Athena.Built for running complex queries that can involve multiple data sources.Must specify S3 bucket location for data.Can immediately begin queries on data in Amazon S3.Must manually load data into created tables.Duplication exists only if already contained in S3 datasetsįor a detailed example of each product’s performance, check out this article from Panopoly.If needed, the key must be declared before data is loaded into the warehouse.Supports complex data types like arrays, maps, and structs. Beneficial due to Athena’s convenient data to query structure.Supports several Serializer/Deserializer (SerDe) libraries for parsing data from different data formats: CSV, JSON, TSV, Parquet, and ORC.Supports UDFs with scalar and aggregate functions.Does not support arrays or object identifier types.Supports several Serializer/Deserializer (SerDe) libraries for parsing data from different data formats: CSV, JSON, TSV, and Apache logs.Can partition by any key with up to 20,000 per table.
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