Amazon Redshift Reviews

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Anonymous | TrustRadius Reviewer
February 25, 2020

Amazon Redshift is an excellent scalable solution for your data warehouse needs.

Score 9 out of 10
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Pros and Cons

  • Replication is excellent, we did not have to worry about reliability.
  • Their auto-scaling feature came to our rescue when it came to cost management.
  • It became expensive over time as the data increased over time.
  • It could not separate users from using the same infrastructure.
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Arthur Zubarev | TrustRadius Reviewer
October 10, 2019

Amazon Redshift Review

Score 8 out of 10
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Pros and Cons

  • Data retrieval experience really gets improved.
  • In terms of database management, it is really a no management at all in AWS. There is no even an OS to take care or worry about.
  • Auto or on-demand scaling is nice.
  • Integrates quite well with other products within the AWS ecosystem.
  • The number of connections is too small, I think at around 50 are allowed in parallel. With some ETL and apps connecting all the time, this brings an undesired possibility to some users or tools being unable to connect.
  • Needs some tuning.
  • The logging part is almost nonexistent.
  • Can be quite costly in the long run as opposed to just RDS or on-prem/dedicated solutions.
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Akshaya Bhardwaj | TrustRadius Reviewer
July 09, 2019

Amazon RedShift is great if you have multiple data channel sources

Score 8 out of 10
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Pros and Cons

  • We can connect with multiple servers and can fetch the data easily from one server to other.
  • It supports the syntax of the bots of the SQL servers, MS SQL and Oracle SQl. This makes it pretty handy to use.
  • Here we use views instead of tables, so we can clearly see the flow of data.
  • It works very slow in the cloud environment.
  • No statistical inbuilt functions are available within the tool.
  • Its user interface is not very attractive.
  • Often it goes into deadlock state, which kills the running jobs.
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Vibhakar Prasad | TrustRadius Reviewer
June 17, 2019

Redshift is awesome!

Score 10 out of 10
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Pros and Cons

  • We reduced the number of Salesforce licenses— Engineering, Sales and Marketing guys are happy to query data from Redshift.
  • Very fast to provide a huge data set with complicated measure.
  • Some of the calculations failed in Salesforce. Redshift returns with the same calculations very fast.
  • Very easy to maintain, no need to worry about hardware failure.
  • We are not able to modify column size.
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Jacob Biguvu | TrustRadius Reviewer
June 08, 2019

Amazon Redshift: easy, simple, fast

Score 8 out of 10
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Pros and Cons

  • User-experience. The user wants something quick to view the output, rather than spending too much time
  • preparing a code prior to seeing the output. Redshift provides SQL type queries. This makes any user happy and comfortable.
  • Architecture is very straightforward and simple to understand, such as MPP architecture, Encryption, and Columnar database design. We can easily address issues and help others to understand.
  • Scalability. We can scale-up and scale-down based on our workloads.
  • Performance tuning and database optimization can be done using the system tables and advisors. These solutions are similar to the solution available for Oracle SQL Server. It makes it easy to do the optimization for queries and databases.
  • The concurrency and scale up based on it could be improved. It would be good if it scale-up and scale-down the memory/CPU capacity automatically based on workload.
  • Often we experience slow on queries and dashboards. Self-tuning option in WLM does help.
  • Optimizing the areas such as Vacuum and reorganize the column data (sorting over time) automatically.
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Anonymous | TrustRadius Reviewer
November 30, 2019

Redshift Review

Score 2 out of 10
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Pros and Cons

  • Fixed cost.
  • Tunable table design.
  • Need to provision warehouse for highest capacity.
  • No real separation between computing and storage (even when considering Spectrum).
  • All users share the same infrastructure resulting in frequent 100% utilization error messages.
  • A leader node can become a bottleneck for too many concurrent aggregate queries.
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Anonymous | TrustRadius Reviewer
September 27, 2019

Redshift is way too easy!

Score 9 out of 10
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Pros and Cons

  • Since it's part of AWS it is fairly quick and easy to set up.
  • You can add nodes fairly quick to expand the data needs.
  • Performance from the analytics reports accessing Redshift is really good.
  • Better database management when looking up table metadata or sizes of tables.
  • Need a better query analyzer.
  • Finding errors during a data load can be a little daunting at times.
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Anonymous | TrustRadius Reviewer
June 15, 2019

Start a data warehouse today with Redshift!

Score 8 out of 10
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Pros and Cons

  • It's fast for data analytics across multiple columns.
  • Essentially, it's good for big datasets.
  • By using RedShift you're kind of married to using AWS's other services, e.g. Redash.
  • You need your data in the cloud.
  • No separate storage and computing.
  • No structured data types.
  • Doesn't scale easily.
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Anonymous | TrustRadius Reviewer
June 13, 2019

Great Analytic Data-Warehouse

Score 10 out of 10
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Pros and Cons

  • Complex queries
  • Aggregation
  • Fully managed service
  • Works very well with most BI/reporting solutions
  • Stored procedures
  • Job scheduling
  • A easier way (perhaps a GUI) to manage users permission
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Brendan McKenna | TrustRadius Reviewer
February 01, 2019

Amazon RedShift happy user

Score 9 out of 10
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Pros and Cons

  • Extremely fast querying allowing for concurrent analysis.
  • PostgreSQL syntax which allows for developers with a SQL background to easily begin working with the data.
  • Multiple output formats including JSON.
  • Safe, easy, and reliable backups.
  • SQL syntax support is not 100% which can lead to frustrating situations when developing a query.
  • No support for database keys.
  • No stored procedure support.
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Anonymous | TrustRadius Reviewer
May 14, 2019

smooth implementation and Quicker reports/dashboards

Score 9 out of 10
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Pros and Cons

  • Easy to work with
  • Seamless implementation with matillion
  • Massive data reads and inserts
  • I didn't like the security aspect of this where it asks us to create views for each customer.
  • It does not support row-level controls.
  • Some SQL queries are faster on native SQL than here. But it could be the data conversions that is causing it.
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Anonymous | TrustRadius Reviewer
December 19, 2018

Amazon Redshift - a new generation of data warehouse platform

Score 8 out of 10
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Pros and Cons

  • It does very well in data ingestion, and compresses data efficiently.
  • Most of the queries return results quickly even with large data sets.
  • It has a hard limit of total number of concurrent connections to the database. Compared with conventional databases that limit is very low.
  • Its workload management (WLM) mechanism could be improved, such as made more dynamic and easier to tune and manage.
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Gavin Hackeling | TrustRadius Reviewer
October 12, 2018

A hands-free data warehouse

Score 8 out of 10
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Pros and Cons

  • Redshift is fully managed. Small teams do not have the resources to maintain a cluster. CloudWatch metrics are provided out-of-the-box, and it is easy to configure alarms.
  • Redshift's console allows you to easily inspect and manage queries, and manage the performance of the cluster.
  • Redshift is ubiquitous; many products (e.g., ETL services) integrate with it out-of-the-box.
  • Writing .csvs to S3 and querying them through Redshift Spectrum is convenient.
  • We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch.
  • Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types.
  • Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables.
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Kyle Reichelt | TrustRadius Reviewer
November 25, 2018

Great for "Big Data" -- but not so much otherwise

Score 7 out of 10
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Pros and Cons

  • If you need draw insights from immense amounts (see: petabytes) of transactional (repetitive) data in near real time--think machine learning and business intelligence--and you're already in the AWS ecosystem, then it's your only real option. It performs very well.
  • Highly configurable, intelligent compression of repetitive columns reduces your memory footprint, lending to extremely high performance.
  • As with most things in the AWS ecosystem, it scales seamlessly and endlessly.
  • There is no support for data de-duplication; meaning this has to be either accounted for upstream, or you'll have to build your own services to de-dupe your data.
  • It's strength is housing data, not necessarily data insertions. While it has an SQL-like interface, it shouldn't be approached the same as a typical relational database.
  • Permissions can be a pain... dovetailing on my previous "con" , in some instances it's easier to drop/rebuild a table than try to navigate incremental updates/insertions, but retaining user-permissions is a pain-point.
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Tamás Imre | TrustRadius Reviewer
February 06, 2018

Amazon Redshift: a fast, scalable and easy to use data warehouse service

Score 9 out of 10
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Pros and Cons

  • It is easy to use. SQL is one of the easiest languages to learn.
  • Fast. Especially if you use an SSD cluster.
  • Scalable. If you need more space for your data or want faster results you can add more nodes.
  • It is PostgreSQL. I miss some commands and procedural features.
  • It is perfect for analytics purposes, but not fast enough for web apps.
  • Too expensive for ETL processing.
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Yogen Sanghani | TrustRadius Reviewer
February 01, 2018

On-prem DW to Redshift

Score 10 out of 10
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Pros and Cons

  • Very fast, parallelized data loading from S3
  • Full ANSI SQL support
  • Highly scalable
  • Columnar storage
  • Does not scale automatically. Need to be scaled up/down manually by adding/removing nodes
  • Does not have support for row level access control
  • Charged based on provisioned capacity - not based on usage
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Michael Romm | TrustRadius Reviewer
September 13, 2017

After Four Months with Redshift

Score 6 out of 10
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Pros and Cons

  • Redshift seems to be as fast processing a large dataset as it is with a small one. It seems, when the dataset size is significantly increased (10x, 100x, 1000x, etc.), DML queries are often executed within the same amount of time.
  • Redshift has a powerful graphical admin tool to monitor the ongoing queries in real time and historically.
  • Easily expandable capacity. Automatic snapshots that eliminate the need for managing backups. Simple database maintenance strategies with the VACUUM and ANALYZE commands.
  • Abundance of detailed documentation and tutorials.
  • It could benefit from adding data integrity and programming tools common to other database management systems.
  • Amazon Redshift is based on PostgreSQL 8.0.2. That version of PostgreSQL was released in December 2006. While PostgreSQL was much improved since then, the new features were not implemented in Redshift. Many basic features are missing from it.
  • Primary keys can be declared but not enforced. Referential integrity (foreign keys) can be declared but not enforced. UNIQUE and CHECK constraints are not supported and cannot be declared.
  • IDENTITY can be declared on a column, and Redshift will put unique values into it. However: IDENTITY values in the newly inserted rows won’t be incremental or sequential. To implement a sequential number, you need to write your own custom code.
  • There are no stored procedures in Redshift. We are writing SQL script files, and then parsing and running them one statement at a time from a Python program. This also enabled us to implement execution-time error logging.
  • In SQL scripts, to check for the row count of affected rows, a complicated join query against some system tables or views has to be executed.
  • Data Control Language (DCL) does not exist. No statements like IF, WHILE, DO, RAISERROR, etc.
  • On performance of views… Views do not “pass-through” a query parameter which is a potential problem for performance.
  • When selecting against a view with the WHERE clause outside of the view, the inner query of the view will be executed first without consideration for the WHERE clause, and only then the WHERE clause will be applied.
  • Certain clauses of SQL work many times faster than other clauses. So be careful and test your statements for performance earlier rather than later, especially if working with a large data set.
  • There was a situation when DELETE FROM JOIN was unacceptably slow. Replacing JOIN with the USING clause made DELETE instantaneous.
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Vinaybabu Raghunandha Naidu | TrustRadius Reviewer
October 12, 2017

Scalable and cost-effective data warehousing tool

Score 7 out of 10
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Pros and Cons

  • Scalability with less downtime.
  • Performance optimization without affecting the business i.e zero downtime during optimization
  • Powerful yet simple to use. Very easy to optimize and improve performance during the regular read/write operations
  • No need of DBA to operate and maintain Redshift as it is a completely managed data warehousing tool
  • Good customer support and will respond in very quick time with clear information and documentation
  • Well documented commands
  • Can propose better optimization techniques based on the business use case.
  • Can provide option to set the upper bound on number of connections to cluster
  • Can improve on optimized writes/updates
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Seth Goldberg | TrustRadius Reviewer
August 01, 2016

Great data warehouse for the money!

Score 8 out of 10
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Pros and Cons

  • Fast analytical queries. The shared nothing and column oriented architecture makes querying very quick compared to databases like Oracle that are designed for OLTP. Scaling is a synch since you can scale out by adding more nodes.
  • Easy table modelling. The only tough decisions you have to make are what your distribution schemes and sort keys are going to be. This is a lot easier than defining partition and index schemes in databases like Oracle or MySQL.
  • Not much maintenance. Almost everything is managed by Amazon. The only exception is table vacuuming and analysis. I was able to program simple ETL jobs to perform this.
  • Works with pretty much anything that works with Postgres. It's hard to find a tool that it isn't compatible with.
  • Lack of enforced constraints (except NOT NULL column constraints). You have to be very careful in your testing to make sure that you aren't duplicating rows.
  • No stored procedure support. Everything must be accomplished through ETL
  • Write operations are very slow and complex.Native SQL row level INSERT and UPDATE statements take an extremely long time to execute. In order to get around this for external data that needs to be loaded, you have to bulk load the data from a flat file to a stage table, then upsert the data from the stage table to your destination table. For data already present in the database, ELT is the only viable way of transforming the data.
  • No good native data modelling tools.
  • Random nondescript errors happen occasionally. The error messages are not decipherable and forums will have no clues as to what happened. It is just a fact of life.
  • No trigger support.
  • OLTP style queries are painfully slow. Don't even think about using Redshift for OLTP...
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Anonymous | TrustRadius Reviewer
November 21, 2017

Best Analytics Cloud Data Warehouse Database

Score 10 out of 10
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Pros and Cons

  • It's a columnar data storage architecture and which allows it to particularly run structured data query for reporting very fast.
  • We used amazon redshift cloud datawarehouse with Tableau, looker reporting tool and it has perfectly helped our reporting needs for business users.
  • Very easy to copy data from Amazon Web Services S3 storage container to Redshift Database with simple copy statements.
  • It provides built-in commands to table structure effectively with less use of memory.
  • AWS can provide some cheaper options with pre core cpu purchase rather than hourly charges on amazon redshift.
  • There are no options for on-premise set-up of the amazon redshift database.
  • Limited documentation on best practices for dist key, sort key and various amazon redshift specific commands.
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Anonymous | TrustRadius Reviewer
June 23, 2017

Amazon Redshift is a widely used tool, and a good choice for many organizations.

Score 9 out of 10
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Pros and Cons

  • It is built out and widely used, which makes it easier to debug and learn.
  • Cheap to store and query.
  • PostgreSQL makes it easier to query.
  • We'd like to get streaming live data.
  • Compute and storage are connected, which can waste CPU.
  • Loading the data into Redshift can be challenging.
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Anonymous | TrustRadius Reviewer
August 10, 2016

Redshift review for the analytics environment

Score 8 out of 10
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Pros and Cons

  • Flexible, OLAP queries.
  • Fast query time (in the order of seconds for most).
  • Standard SQL language.
  • Fast ways to insert more data.
  • VACUUM is a pain, its unclear exactly how often it needs to be done.
  • Redshift has a limit on how many concurrent writes and reads you can do that won't scale to 100s of people using it.
  • Redshift lacks some Postgres queries that make some standard SQL operations hard.
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Anonymous | TrustRadius Reviewer
August 05, 2016

get started with columnar databases easily with AWS Redshift

Score 7 out of 10
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Pros and Cons

  • AWS infrastructure and support simplifies maintenance and administration
  • familiarity with PostgreSQL makes adopting Redshift as a column store easier
  • columnar data store allows for high performance queries on large volumes of data
  • there are some situations where having a column store more closely integrated as part of our platform would be better
  • AWS costs can add up
  • many other (open source) column stores have new and interesting features not (yet) available in Redshift
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About Amazon Redshift

Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
Categories:  Data Warehouse

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