What users are saying about
Top Rated
110 Ratings
Top Rated
144 Ratings
Top Rated
77 Ratings
Top Rated
110 Ratings
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Score 8.7 out of 100
Top Rated
144 Ratings
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Score 8.1 out of 100
Top Rated
77 Ratings
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Score 9.2 out of 100

Likelihood to Recommend

Google BigQuery

BigQuery is unlike anything we've used as a big data tool. It is perfectly suited to query large data sets quickly and to store those large data sets for any time use. It's perfect for storing data and using it for reports. Logging data is the perfect application for BigQuery, but transactional data is possible as well
Tristan Dobbs | TrustRadius Reviewer

Amazon Redshift

If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)
Arthur Zubarev | TrustRadius Reviewer

Snowflake

Snowflake is great when you need to store large amounts of data while retaining the ability to query that data quickly. It is very reliable and allows for auto-scaling on large queries meaning that you're only paying for the power you actually use. It's taken queries that took 20+ minutes to run on redshift down to 2 minutes on Snowflake.
Jake Schlingman | TrustRadius Reviewer

Feature Rating Comparison

Database-as-a-Service

Google BigQuery
9.0
Amazon Redshift
Snowflake
Automatic software patching
Google BigQuery
9.3
Amazon Redshift
Snowflake
Database scalability
Google BigQuery
9.4
Amazon Redshift
Snowflake
Automated backups
Google BigQuery
8.7
Amazon Redshift
Snowflake
Database security provisions
Google BigQuery
8.8
Amazon Redshift
Snowflake
Monitoring and metrics
Google BigQuery
8.8
Amazon Redshift
Snowflake
Automatic host deployment
Google BigQuery
9.0
Amazon Redshift
Snowflake

Pros

Google BigQuery

  • How many pros can a person type? This storage program gives workers and students the reality of unlimited storage space. I have never came close to overfilling my google cloud storage because it's huge and the best. I can view anything I save on there from any of my internet devices which is very important.
  • Depending on how you have the program set up - either online or through an application that lives on your desktop, dragging and dropping files to and from Cloud Storage couldn't be any more uncomplicated. Plus, new users who meet certain criteria - like updating personal security, or share the program receive additional free online storage.
  • The array of tools is very impressive, intuitive to use, and well organized in the sense that you don't have to go looking for individual apps. They're all easily accessed via a single dropdown.
Sam Lepak | TrustRadius Reviewer

Amazon Redshift

  • 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.
Gavin Hackeling | TrustRadius Reviewer

Snowflake

  • Impressive data retrieval and data compression ratio.
  • Semi-structured data (JSON, XML) can be loaded as is and retrieved in a tabular structure on the fly using the flatten function.
  • Zero-copy cloning is an excellent feature which saves hours to refresh latest data in development instance.
  • Extensive usages documentation with examples makes development easy.
Anonymous | TrustRadius Reviewer

Cons

Google BigQuery

  • Though it is SQL some syntax are different but they are getting used to after you use for some time.
  • The legacy SQL is in beta state but can be used and you can run the query with simple SQL.
  • More documentation is needed for using User-defined functions in Big Query.
Anonymous | TrustRadius Reviewer

Amazon Redshift

  • 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.
Michael Romm | TrustRadius Reviewer

Snowflake

  • Very limited amount of tabs - saved queries, which requires us to store the code somewhere else and re-use existing queries.
  • Performance can really be a problem if there are many users on the system at the same time.
  • SnowFlake support sometimes can be hard to reach.
Anonymous | TrustRadius Reviewer

Likelihood to Renew

Google BigQuery

No score
No answers yet
No answers on this topic

Amazon Redshift

No score
No answers yet
No answers on this topic

Snowflake

Snowflake 8.0
Based on 1 answer
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
Anonymous | TrustRadius Reviewer

Usability

Google BigQuery

Google BigQuery 9.0
Based on 1 answer
BigQuery is a little bit difficult to learn at first. The tools are all there but it takes a few hours of practice and trial and error to be comfortable processing a large dataset. It can handle quite a bit and the cloud storage makes those experimental practice hours much easier to do in your spare time. The software is capable of doing a lot, it's just a matter of being patient and learning the ways of BigQuery.
Anonymous | TrustRadius Reviewer

Amazon Redshift

Amazon Redshift 8.5
Based on 8 answers
Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
Brendan McKenna | TrustRadius Reviewer

Snowflake

Snowflake 8.7
Based on 11 answers
The web front end is OK, but they could improve the product with a front end GUI. We have connected DBEAVER to snowflake with an ODBC driver, but the queries are a lot slower from DBEAVER, compared to the web front end. SSIS also has an ODBC connection, but it is also a slower to pull data from snowflake. Overall the usability is good.
Wicks Justin | TrustRadius Reviewer

Support Rating

Google BigQuery

Google BigQuery 8.5
Based on 16 answers
I rated the overall support for Google BigQuery as a mediocre five because it has limited support from Google. Instead, it is heavily dependent on an organization's IT resources such as SQL analysts and Data Architects to run big data reports or maintain data quality. Additionally, if errors occur during a run of complex SQL queries or when sending data to Google BigQuery from other sources, Google provides basic email support which needs to be complemented with internal data warehouse support to fix the root cause of the database errors. Finally, due to constraints on the amount of data an analyst can query or pay the additional cost when exceeding the limit, basic Google support is not sufficient to meet data needs without interruption.
Anonymous | TrustRadius Reviewer

Amazon Redshift

Amazon Redshift 7.4
Based on 6 answers
The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support
Anonymous | TrustRadius Reviewer

Snowflake

Snowflake 8.5
Based on 10 answers
Overall, the support from Snowflake has been very good. Since we are one of the major users for Snowflake and have a dedicated tech team to solve all the technical problem on our way. On the side of the technical problem, any sql related questions can be found from everywhere online.
Anonymous | TrustRadius Reviewer

Alternatives Considered

Google BigQuery

Spinning up, provisioning, maintaining and debugging a Hadoop solution can be non-trivial, painful. I'm talking about both GCE based or HDInsight clusters. It requires expertise (+ employee hire, costs). With BigQuery if someone has a good SQL knowledge (and maybe a little programming), can already start to test and develop. All of the infrastructure and platform services are taken care of. Google BigQuery is a magnitudes simpler to use than Hadoop, but you have to evaluate the costs. BigQuery billing is dependent on your data size and how much data your query touches.
Csaba Toth | TrustRadius Reviewer

Amazon Redshift

Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
Anonymous | TrustRadius Reviewer

Snowflake

The average percentage of time that a data warehouse is actually doing something is around 20%. Given this, the price by query estimate becomes an important pricing consideration. For this, Snowflake crucially decouples of storage and compute. With Snowflake you pay for 1) storage space used and 2) amount of time spent querying data. Snowflake also has a notion of a “logical warehouse” which is the “compute” aspect of the database. These warehouses can be scaled up or down to deliver different grades of performance. You can also configure the number of compute nodes to parallelize query execution. These warehouses can be configured to “pause” when you’re not using them for cost efficiency. As a result, you can have a super beefy warehouse for BI queries that’s only running when people are using your BI tools, while your background batch jobs can use cheaper hardware.
Andrew Goss | TrustRadius Reviewer

Return on Investment

Google BigQuery

  • Google BigQuery has had enormous impact in terms of ROI to our business, as it has allowed us to ease our dependence on our physical servers, which we pay for monthly from another hosting service. We have been able to run multiple enterprise scale data processing applications with almost no investment
  • Since our business is highly client focused, Google Cloud Platform, and BigQuery specifically, has allowed us to get very granular in how our usage should be attributed to different projects, clients, and teams.
  • Plain and simple, I believe the meager investments that we have made in Google BigQuery have paid themselves back hundreds of times over.
Alex Andrews | TrustRadius Reviewer

Amazon Redshift

  • Redshift has had a very positive impact on our business. It has been used to provide analytics on marketing campaigns to boost revenue.
  • Redshift is instrumental in our payment collection business processes. It powers everything from who gets called to who gets sent collection emails.
Seth Goldberg | TrustRadius Reviewer

Snowflake

  • Quick installation/setup for a data warehouse solution.
  • Make easy to handle/manage the various type of semi-structured data using the native solutions and provided new data modeling concepts such as schema-read data model and schema-write data model.
  • Make easy and simplified the workload management using virtual warehouses and materialized views.
Jacob Biguvu | TrustRadius Reviewer

Pricing Details

Google BigQuery

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Amazon Redshift

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Snowflake

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Rating Summary

Likelihood to Recommend

Google BigQuery
8.6
Amazon Redshift
8.0
Snowflake
9.2

Likelihood to Renew

Google BigQuery
Amazon Redshift
Snowflake
8.0

Usability

Google BigQuery
9.0
Amazon Redshift
8.5
Snowflake
8.7

Support Rating

Google BigQuery
8.5
Amazon Redshift
7.4
Snowflake
8.5