We performed a comparison between BigQuery and TIBCO Live Datamart based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"As a cloud solution, it's easy to set up."
"The integrated data storage features are good."
"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."
"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."
"When integrating their system into the cloud-based solutions, we were able to increase their efficiency and overall productivity twice compared with their on-premises option."
"The product is serverless. We only need to write SQL queries to analyze the data. We need to pay based on the number of queries. The retrieval time is very less. Even if you write large queries, the tool is able to bring back data in a few seconds."
"One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."
"The solution has a powerful aggregating feature"
"You can create your own rules that include mathematic calculations."
"Some of the queries are complex and difficult to understand."
"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."
"We'd like to have more integrations with other technologies."
"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."
"I understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."
"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."
"It would be helpful if they could provide some dashboards where you can easily view charts and information."
"I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."
"Improvements need to be made on the load balancing side."
"The solution's setup could be quicker and easier."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while TIBCO Live Datamart is ranked 12th in Data Warehouse with 2 reviews. BigQuery is rated 8.2, while TIBCO Live Datamart is rated 9.0. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of TIBCO Live Datamart writes "Standout features are real-time dashboards and powerful aggregation". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Vertica and Apache Hadoop, whereas TIBCO Live Datamart is most compared with . See our BigQuery vs. TIBCO Live Datamart report.
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