An AWS Glue connector for accessing Exasol database
Overview
An AWS Glue Studio connector for accessing Exasol database. You can use it to perform read or write operations to Exasol database from AWS Glue Studio.
Highlights
- Supports reading, writing, column projection and predicate pushdown
Details
Sold by
Delivery method
Delivery option
Activate in AWS Glue Studio
Latest version
Operating system
Linux
Pricing
This product is free. Subscriptions have no end date and can be canceled anytime.
Vendor refund policy
This is a placeholder value. Please update this value via the AWS Marketplace Management Portal.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Activate in AWS Glue Studio
Supported services: Learn more
- Amazon ECS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
Exasol AWS Glue Connector 2.0.0, released 2023-03-08
Code name: AWS Glue Version 4.0.0
Summary
In this release we updated support for the latest AWS Glue Studio 4.0.0 release.
It supports the Spark 3.3.0 and Python 3.10 versions. Here are some notable improvements:
- Many Spark functionality upgrades from Spark 3.1 to Spark 3.3
- Log4j 2 migration from Log4j 1.x
- Several Python module updates from AWS Glue 3.0, such as an upgraded version of Boto
- Native support for open-data lake frameworks with Apache Hudi, Delta Lake, and Apache Iceberg
- Native support for the Amazon S3-based Cloud Shuffle Storage Plugin (an Apache Spark plugin) to use Amazon S3 for shuffling and elastic storage capacity
You can read more about the changes on the release notes .
Refactorings
- #66: Updated to AWS Glue version
4.0.0 - #64: Updated dependencies and removed references to
maven.exasol.comrepository
Dependency Updates
Compile Dependency Updates
- Updated
com.exasol:exasol-jdbc:7.1.11to7.1.17 - Added
com.fasterxml.woodstox:woodstox-core:6.5.0 - Updated
software.amazon.awssdk:s3:2.18.4to2.20.19
Test Dependency Updates
- Updated
com.amazonaws:AWSGlueETL:3.0.0to4.0.0 - Updated
com.amazonaws:aws-java-sdk-s3:1.12.329to1.12.422 - Updated
com.exasol:exasol-testcontainers:6.3.0to6.5.1 - Updated
com.exasol:java-util-logging-testing:2.0.2to2.0.3 - Updated
com.exasol:test-db-builder-java:3.4.1to3.4.2 - Removed
log4j:log4j:1.2.17 - Updated
nl.jqno.equalsverifier:equalsverifier:3.10.1to3.14 - Added
org.apache.logging.log4j:log4j-api:2.20.0 - Added
org.apache.logging.log4j:log4j-core:2.20.0 - Updated
org.junit.jupiter:junit-jupiter-api:5.9.1to5.9.2 - Updated
org.junit.jupiter:junit-jupiter:5.9.1to5.9.2 - Updated
org.mockito:mockito-core:4.8.1to5.1.1 - Updated
org.mockito:mockito-junit-jupiter:4.8.1to5.1.1 - Updated
org.testcontainers:junit-jupiter:1.17.5to1.17.6 - Updated
org.testcontainers:localstack:1.17.5to1.17.6
Plugin Dependency Updates
- Updated
com.exasol:error-code-crawler-maven-plugin:1.1.2to1.2.2 - Updated
com.exasol:project-keeper-maven-plugin:2.8.0to2.9.3 - Updated
io.github.zlika:reproducible-build-maven-plugin:0.15to0.16 - Updated
org.apache.maven.plugins:maven-assembly-plugin:3.3.0to3.4.2 - Updated
org.apache.maven.plugins:maven-failsafe-plugin:3.0.0-M5to3.0.0-M8 - Updated
org.apache.maven.plugins:maven-jar-plugin:3.2.2to3.3.0 - Updated
org.apache.maven.plugins:maven-shade-plugin:3.4.0to3.4.1 - Updated
org.apache.maven.plugins:maven-surefire-plugin:3.0.0-M5to3.0.0-M8 - Updated
org.codehaus.mojo:flatten-maven-plugin:1.2.7to1.3.0 - Updated
org.codehaus.mojo:versions-maven-plugin:2.10.0to2.14.2
Additional details
Usage instructions
Please subscribe to the product from AWS Marketplace and Activate the Glue connector from AWS Glue Studio
Support
Vendor support
Please let us know by opening support ticket at https://www.exasol.com/support Or by opening Github issue at project repository
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
Exasol is the fastest in-memory MPP database according to the TPC-H benchmark for clustered, decision support databases (up to 1.6 million queries per hour). It is designed specifically for BI, analytics and reporting and scales rapidly from 10's GBs to 100's TBs.
EXASOL is the high-performance, in-memory, MPP database specifically designed for analytics. Exasol SaaS expands your deployment choices and now means you can experience award winning analytics performance wherever you need it on-premises, in the Cloud of your choice, or as-a-service.
Yotilla
By EXASOL AG
Yotilla is a data warehouse (DWH) automation service for Exasol, Snowflake and AWS Redshift. With Yotilla you can significantly speed up the creation and management of DWH. Yotilla fully automates the Data Vault and Data Mart layers. This also includes modeling the Data Vault so that Data Vault expertise is no longer required.
Kickstarter: Exasol on AWS
By b.telligent
In our Kickstarter project, we will show you how Exasol can deliver your data analytics requirements and we will walk you through the first steps of your data analytics journey with Exasol on AWS.
Profit from our best practices, implementation experience and rapid deployment of an AWS Cloud Dataplatform with Exasol.
Customer reviews
Okan .
Review
Reviewed on Jun 14, 2022
Review provided by G2
What do you like best about the product?
It has a great speed compare to other analytics DB providers
What do you dislike about the product?
It's a low level of consultancy and low level of market knowledge
What problems is the product solving and how is that benefiting you?
We have a huge data thats why we need a great product at speed and exasol doing it very good
Recommendations to others considering the product:
It's great db for analytics solution, needs much more atention and very similar syntax to Oracle with can unlock migrations
Leave a comment0 comments
Hugo V.
The best Analytic Database performance
Reviewed on Jun 12, 2021
Review provided by G2
What do you like best about the product?
The Performance is the best of market,never I could see an Analytic Database with this Performance
What do you dislike about the product?
I believe that Exasol needs more marketing.
What problems is the product solving and how is that benefiting you?
Load data near real time, performance to see strategics dashboards.
Josip C.
Best analytics DB
Reviewed on Mar 23, 2021
Review provided by G2
What do you like best about the product?
Easy to use and build complex SQL queries. Performance on it is fantastic.
It is also great, that it can handle multiple users to work on the same dataset without any problems with performance.
Great tool
It is also great, that it can handle multiple users to work on the same dataset without any problems with performance.
Great tool
What do you dislike about the product?
Initially had problems loading data via Alteryx but switching to the ExaLoader created lightning fast bulk load solution.
What problems is the product solving and how is that benefiting you?
We are building reporting on top of it and doing ad-hoc analysis.
Speed is phenomenal even when running complex queries.
Speed is phenomenal even when running complex queries.
Vitaly M.
Best choice for on-premise, getting better in the cloud
Reviewed on Mar 12, 2021
Review provided by G2
What do you like best about the product?
+ Amazing performance in general;
+ Cost-to-performance ratio is very competitive, you'll need much less hardware;
+ Efficient indexed JOINs, probably best in class;
+ Flexible UDF scripts, can be implemented in any programming language and run in parallel;
+ Cost-to-performance ratio is very competitive, you'll need much less hardware;
+ Efficient indexed JOINs, probably best in class;
+ Flexible UDF scripts, can be implemented in any programming language and run in parallel;
What do you dislike about the product?
- Lack of native support for composite data types;
- Lack of native partial backup (per-table, per-schema), must use EXPORT instead;
- Detection of data lineage is a bit difficult, unless you implement it yourself externally;
- Cloud capabilities are not fully utilised (yet), but it's not a problem for "on-premise";
- Lack of native partial backup (per-table, per-schema), must use EXPORT instead;
- Detection of data lineage is a bit difficult, unless you implement it yourself externally;
- Cloud capabilities are not fully utilised (yet), but it's not a problem for "on-premise";
What problems is the product solving and how is that benefiting you?
Self-service analytics, ad-hoc queries, financial reporting, data-driven internal products (e.g. A/B testing, forecasting), machine learning.
Ricardo G.
A high-performance database for Analytics. Would definitely recommend it.
Reviewed on Mar 08, 2021
Review provided by G2
What do you like best about the product?
My first experience with Exasol was revealing: when migrating our data warehouse we saw many reports running in 1/10 of the time.
This extraordinary performance allowed to, over time, squeeze much more value from the database, while keeping low maintenance and development costs.
For my Analytics department, migrating to Exasol was the single most important step that we took to provide a better service to business, assure quick development cycles and incur in minimal admin effort.
This extraordinary performance allowed to, over time, squeeze much more value from the database, while keeping low maintenance and development costs.
For my Analytics department, migrating to Exasol was the single most important step that we took to provide a better service to business, assure quick development cycles and incur in minimal admin effort.
What do you dislike about the product?
Scripting capabilities can be enhanced and better documented. It is not always easy to find resources capable to program with Lua scripting.
What problems is the product solving and how is that benefiting you?
We are building a wide set of Analytics solutions, including customer profiles, data science models, stock optimization solutions and Dashboards. Each provide a relevant business impact within the organization.