Likelihood to Recommend For organizations looking to avoid the overhead of managing infrastructure, BigQuery's server-less architecture allows teams to focus on analyzing data without worrying about server maintenance or capacity planning. Small projects or startups with limited data analysis needs and tight budgets might find other solutions more cost-effective. Also, it is not suitable for OLTP systems.
Read full review SingleStore HTAP engine is well suited for real-time analytics, fast ingestion, scaling OLTP system like
MySQL . When you need to run reports or perform aggregates on billions of rows and you get result in seconds, you cannot get this experience with other OLTP engines. I wish DBtLab was a little more developer and supported for SingleStore. This would allow to perform better data transformation. You can use stored procedures, but DBTLabs has become a standard for dimensional modeling in data warehousing projects. This is probably why SingleStore has trouble piercing in the data warehouse world. It is definately capable to compete with
Snowflake when it comes to scalability, query performance, data compression, but
Snowflake has ravaged the data warehouse market in few years and large corporations have already invested lots of money in migrating into
Snowflake . The SingleStore community needs to grow. Everyone who uses SingleStore loves it.
Read full review Pros Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data. Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns. Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds. Read full review Technical support is stellar -- far above and beyond anything I've experienced with any other company. When we compared SingleStore to other databases two years ago, we found SingleStore performance to be far superior. Pipeline data ingestion is exceptionally fast. The ability to combine transactional and analytical workloads without compromising performance is very impressive. Read full review Cons Can't use it out of Google's cloud platform which is a minus point if you want a local setup. Can be a little expensive to manage. A little difficult to manage someone with less technical expertise as it requires you to have SQL knowledge of joins, CTEs etc. Read full review We wish the product had better support for High Availability of the aggregator. Currently the indexes generated by the two different aggregators are not in the same sequential space and so our apps have more burden to deal with HA. More tools for debugging issues such as high memory usage would be good. The price was the one that kept us away from purchasing for the first few years. Now we are able to afford due to a promotion that gives it at 25% of the list price. Not sure if we'll continue after the promotion offer expires in another 2 years. Read full review Likelihood to Renew We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
Read full review We haven't seen a faster relation database. Period. Which is why we are super happy customers and will for sure renew our license.
Read full review Usability web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
Read full review [Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
Read full review Reliability and Availability We have not experienced any downtime in the two years that we have been using SingleStore.
Read full review Performance SingleStore's performance is incredible. Our predictive algorithms went from taking 24-48 HOURS down to 15 minutes allowing our team to run those much more frequently. Previously, we were limited to about 60 requests per minute due to table locks. Implementing columnstore on SingleStore allowed us to receive 1000 requests per minute.
Read full review Support Rating BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
Read full review Very responsive to trouble tickets - Often, I think, the SingleStore's monitoring systems have already alerted the engineers by the time I get around to writing a ticket (about 10 - 20 mins after we see a problem). I feel like things are escalated nicely and SingleStore takes resolving trouble tickets seriously. Also SingleStore follows up after incidents to with a post mortem and actionable takaways to improve the product. Very satisfied here.
Read full review Implementation Rating We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
Read full review Alternatives Considered Google's
Firebase isn't a competitor but we had to use Google's BigQuery because Google's
Firebase 's database is limited compared to Google's BigQuery. Linking your
Firebase project to BigQuery lets you access your raw, unsampled event data along with all of your parameters and user properties. Highly recommend connecting the two if you have a mobile app.
Read full review Timescale was the biggest alternative option we looked at for SingleStore, however the requirement to learn a new syntax (due to not being SQL compatible) was our biggest pain point. Supporting a new language would require alterations to the Laravel framework, as this only offered SQL integration out of the box. This alteration would be time consuming and would limit our scope to future hiring due to the new syntax.
Read full review Contract Terms and Pricing Model None so far. Very satisfied with the transparency on contract terms and pricing model.
Read full review Scalability We needed more memory on our cluster. SingleStore handled it very smoothly.
Read full review Professional Services Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Read full review Return on Investment 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. Read full review As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data. Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog. Read full review ScreenShots Google BigQuery Screenshots