Apache Pinot vs AWS Glue
Overview
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Detailed Comparison
A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. | Apache Pinot is a fast, scalable real-time analytics database. It is a column-oriented distributed Online Analytics Processing (OLAP) database designed for high concurrency and low latency. It can scan petabyte-scale data and produce results even as fast as single-digit milliseconds. |
Easy - AWS Glue automates much of the effort in building, maintaining, and running ETL jobs. AWS Glue crawls your data sources, identifies data formats, and suggests schemas and transformations. AWS Glue automatically generates the code to execute your data transformations and loading processes.; Integrated - AWS Glue is integrated across a wide range of AWS services.; Serverless - AWS Glue is serverless. There is no infrastructure to provision or manage. AWS Glue handles provisioning, configuration, and scaling of the resources required to run your ETL jobs on a fully managed, scale-out Apache Spark environment. You pay only for the resources used while your jobs are running.; Developer Friendly - AWS Glue generates ETL code that is customizable, reusable, and portable, using familiar technology - Scala, Python, and Apache Spark. You can also import custom readers, writers and transformations into your Glue ETL code. Since the code AWS Glue generates is based on open frameworks, there is no lock-in. You can use it anywhere. | Real-time ingestion (Kafka, Kinesis, Pulsar);
Real-time upserts;
Batch ingestion (Flink, Hadoop, Spark);
SQL ingestion (Snowflake,
BigQuery);
Ingestion time pre-processing (transforms, flattening, rollups);
Flexible indexing types (star-tree, Bloom filter, forward, inverted,
geospatial, JSON, range, text, timestamp);
Automatic data replication and partitioning;
Encryption (on disk; transport);
Easy table management (backfills, dynamic re-indexing, minions for dynamic data layout changes);
Schema evolution;
Nested columns |
Statistics | |
GitHub Stars - | GitHub Stars 5.9K |
GitHub Forks - | GitHub Forks 1.4K |
Stacks 461 | Stacks 5 |
Followers 819 | Followers 3 |
Votes 9 | Votes 0 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
What are some alternatives to AWS Glue, Apache Pinot?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Presto
Distributed SQL Query Engine for Big Data
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
lakeFS
It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
Apache Kylin
Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Apache Impala
Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
Vertica
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.
