Try our new research platform with insights from 80,000+ expert users
BigQuery Logo

BigQuery pros and cons

Vendor: Google
4.1 out of 5

Pros & Cons summary

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.
Get the report

Prominent pros & cons

PROS

BigQuery offers seamless scalability, allowing users to manage vast datasets effortlessly.
BigQuery excels in performance with rapid query processing and efficient data handling.
BigQuery effectively supports standard SQL and performs complex queries on large datasets.
BigQuery leverages machine learning and AI capabilities, enhancing data insights.
BigQuery's architecture efficiently decouples storage and compute for cost-effective management.

CONS

BigQuery has restrictions with special characters during data migration, leading to errors and requiring workarounds like regular expressions.
External tables lack caching capabilities, which results in additional costs compared to native tables that support caching.
The platform is considered expensive, limiting accessibility for small and medium-sized businesses, with affordability being a significant concern.
Migrating data, particularly substantial volumes, to a cloud-based platform like BigQuery presents significant challenges.
The integration of third-party tools and connectors is limited, impacting flexibility and compatibility with other technologies.
 

BigQuery Pros review quotes

Syed WaqasKazi - PeerSpot reviewer
Sep 26, 2023
BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI.
Anonymous  - PeerSpot reviewer
May 9, 2022
The main thing I like about BigQuery is storage. We did an on-premise BigQuery migration with trillions of records. Usually, we have to deal with insufficient storage on-premises, but in BigQuery, we don't get that because it's like cloud storage, and we can have any number of records. That is one advantage. The next major advantage is the column length. We have some limits on column length on-premises, like 10,000, and we have to design it based on that. However, with BigQuery, we don't need to design the column length at all. It will expand or shrink based on the records it's getting. I can give you a real-life example based on our migration from on-premises to GCP. There was a dimension table with a general number of records, and when we queried that on-premises, like in Apache Spark or Teradata, it took around half an hour to get those records. In BigQuery, it was instant. As it's very fast, you can get it in two or three minutes. That was very helpful for our engineers. Usually, we have to run a query on-premises and go for a break while waiting for that query to give us the results. It's not the case with BigQuery because it instantly provides results when we run it. So, that makes the work fast, it helps a lot, and it helps save a lot of time. It also has a reasonable performance rate and smart tuning. Suppose we need to perform some joins, BigQuery has a smart tuning option, and it'll tune itself and tell us the best way a query can be done in the backend. To be frank, the performance, reliability, and everything else have improved, even the downtime. Usually, on-premise servers have some downtime, but as BigQuery is multiregional, we have storage in three different locations. So, downtime is also not getting impacted. For example, if the Atlantic ocean location has some downtime, or the server is down, we can use data that is stored in Africa or somewhere else. We have three or four storage locations, and that's the main advantage.
Shiva Prasad ELLUR - PeerSpot reviewer
Feb 21, 2023
The integrated data storage features are good.
Learn what your peers think about BigQuery. Get advice and tips from experienced pros sharing their opinions. Updated: December 2024.
824,053 professionals have used our research since 2012.
MandarGarge - PeerSpot reviewer
Jun 30, 2022
It has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution.
Matt Costa - PeerSpot reviewer
Jun 16, 2023
It's pretty stable. It's fast, and it is able to go through large quantities of data pretty quickly.
reviewer2264685 - PeerSpot reviewer
Aug 25, 2023
Even non-coders can review the data in BigQuery.
Saqib Manzar - PeerSpot reviewer
Nov 3, 2023
The interface is what I find particularly valuable.
NT
Nov 2, 2023
BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space.
reviewer1473792 - PeerSpot reviewer
May 29, 2022
There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot.
reviewer1998315 - PeerSpot reviewer
Nov 8, 2022
It's straightforward to set up.
 

BigQuery Cons review quotes

Syed WaqasKazi - PeerSpot reviewer
Sep 26, 2023
For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options.
Anonymous  - PeerSpot reviewer
May 9, 2022
It would be better if BigQuery didn't have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise. But in BigQuery, we have huge restrictions. If we have some symbols, like a hash or other special characters, it won't accept them. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. We need to use Regexp or something similar to replace that with another character. This isn't expected from a high-range technology like BigQuery. It has to adapt all products. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. Teradata and Apache Spark accept this, but BigQuery won't. This is the primary concern that we had. In the next release, it would be better if the query on the external table also had cache. Right now, we are using a GCS bucket, and in the native table, we have cache. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. But when we run queries on the external table a number of times, it won't be cached. That's a major drawback of BigQuery. Only the native table has the cache option, and the external table doesn't. If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization.
Shiva Prasad ELLUR - PeerSpot reviewer
Feb 21, 2023
There are some limitations in the query latency compared to what it was three years ago.
Learn what your peers think about BigQuery. Get advice and tips from experienced pros sharing their opinions. Updated: December 2024.
824,053 professionals have used our research since 2012.
MandarGarge - PeerSpot reviewer
Jun 30, 2022
There are many tools that you have to use with BigQuery that are different services also provided for by Google. They need to all be integrated into BigQuery to make the solution easier to use.
Matt Costa - PeerSpot reviewer
Jun 16, 2023
There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans.
reviewer2264685 - PeerSpot reviewer
Aug 25, 2023
The process of migrating from Datastore to BigQuery should be improved.
Saqib Manzar - PeerSpot reviewer
Nov 3, 2023
It would be beneficial to integrate additional tools, particularly from a business intelligence perspective.
NT
Nov 2, 2023
The processing capability can be an area of improvement.
reviewer1473792 - PeerSpot reviewer
May 29, 2022
With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. You have to actually open a ticket and then follow it up with Google support.
reviewer1998315 - PeerSpot reviewer
Nov 8, 2022
We'd like to have more integrations with other technologies.