Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Alkira Network Cloud
Score 9.0 out of 10
N/A
Alkira Network Cloud is a multi-cloud network solution with integrated services, visibility and governance. Alkira's service is hosted in multiple data centers to provide redundancy, and the data centers and virtual exchange points are in geographically distributed regions and deployed in different high availability zones for availability and redundancy.N/A
Google BigQuery
Score 8.7 out of 10
N/A
Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Snowflake
Score 8.7 out of 10
N/A
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.N/A
Pricing
Alkira Network CloudGoogle BigQuerySnowflake
Editions & Modules
No answers on this topic
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
No answers on this topic
Offerings
Pricing Offerings
Alkira Network CloudGoogle BigQuerySnowflake
Free Trial
NoYesYes
Free/Freemium Version
NoYesNo
Premium Consulting/Integration Services
NoNoNo
Entry-level Setup FeeOptionalNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Alkira Network CloudGoogle BigQuerySnowflake
Considered Multiple Products
Alkira Network Cloud

No answer on this topic

Google BigQuery
Chose Google BigQuery
I have used Snowflake and DataGrip for data retrieval as well as Google BigQuery and can say that all these tools compete for head to head. It is very difficult to say which is better than the other but some features provided by Google BigQuery give it an edge over the others. …
Chose Google BigQuery
Google BigQuery is less expensive to run and offers free storage of up to the first 10 GB of data. Google BigQuery is also easier (and faster) to get up and running. Unlike Snowflake, Google BigQuery does not require any manual scaling or performance tuning. Scaling is …
Chose Google BigQuery
Google BigQuery is cheaper and much faster as compared to both. While as compared to Snowflake , we tested it was faster and cheaper by 30%, that is after Snowflake tweaked their environment, if not for that it would have been 90% cheaper than Snowflake. Redshift is not easy …
Chose Google BigQuery
We actually use Snowflake and BigQuery in tandem because they both currently meet various needs. Redshift, however, has barely been used since our migration away from it. In the case of both Snowflake and BigQuery, they beat Redshift by a long shot. The main reasons are their …
Chose Google BigQuery
Fully serverless. We don’t manage clusters or warehouses. Requires us to manage virtual warehouses. BigQuery is cheaper for exploratory heavy queries; Snowflake is more predictable for sustained workloads. BigQuery is unbeatable if you’re deep in Google’s ecosystem; Snowflake
Chose Google BigQuery
Google BigQuery of course collects a much much larger array of raw data and can handle (practically) an unlimited amount of data. For a large enterprise like ours that relies on large-scale analytics, this is absolutely imperative. Google BigQuery can also combine GA4 data with …
Chose Google BigQuery
Compared to every other analytics DB solution I've used, Google BigQuery was by far the easiest to set up and maintain, and scale.
The price was also much lower for our use case (internal data analysis).
Chose Google BigQuery
First and foremost, Google BigQuery's pricing structure, based on data processing and storage, is more cost-effective for our needs. Secondly, since we already use other Google Cloud services, its tight integration with them especially, with Cloud Storage and Dataflow was a big …
Chose Google BigQuery
We based our analysis primarily on [BigQuery vs. Redshift vs. Athena] and BigQuery proved to be the best solution for us.
Chose Google BigQuery
At my previous organization we used server based SQL server. There were days when the server was down and we couldn't work or access the data. This caused multiple reports and processes which were fed from the server to fail. Google BigQuery doesn't have such problems.
Chose Google BigQuery
Both BigQuery and Redshift are two comparable fully managed petabyte-scale cloud data warehouses. They’re similar in many ways, but you should consider their unique features and how they can contribute to an organization’s data analytics infrastructure. When considering which …
Chose Google BigQuery
BigQuery by far the best solution in all angles compared to other ones: Especially scalability, ease of use, performance and there is no need to manage any cluster of servers. Also it's ABSOLUTELY pay as you go! No one in market currently provide such service that can compete …
Snowflake
Chose Snowflake
We particularly liked Snowflake's security model as well as its unique storage (whereby everything is essentially a pointer to immutable micro-partitions, which is the key behind its zero-copy cloning, its secure sharing, its time travel, etc.). and also how it separates …
Chose Snowflake
These are comparable products that can make sense depending on the specific needs of your organization. All are certainly serviceable and have varying pros and cons. Snowflake seems to provide the greatest degree of flexibility and easy scalability as new data gets brought into …
Chose Snowflake
Snowflake has an attractive pricing model with auto-suspend and auto-resume and pay per use. AWS Redshift requires higher administrative efforts to maintain and scale the platform whereas with Snowflake those admin tasks are not needed or automatically taken care of.
Chose Snowflake
Each of the other solutions were cloud vendor specific, Snowflake can ride on either Amazon Web Services, Microsoft Azure, or Google Cloud. The fact that they are ANSI-sql compliant and have an effective means of offloading data makes them portable and easy to sell to teams …
Chose Snowflake
Snowflake has won the match because it is giving an excellent performance with its efficient features and reliable results. This is a totally secure program for our precious and important data.
Chose Snowflake
Snowflake beats these other products in every category it was rated against
Chose Snowflake
In my experience running the data management practice at InterWorks, we believe that cloud data warehouse products will eventually serve the majority of data warehousing use cases and power data analytics at most companies. Of this cohort, we believe that Snowflake is the best …
Chose Snowflake
Our issue with Redshift was that it was very expensive. On top of that, queries were still slow and if we used more of Redshift's memory, then it would have cost even more. Snowflake is not cheap, but less costly for us. Plus, the performance was much better. Also, we got to …
Chose Snowflake
More flexible and faster compared to Redshift, more functionality compared to BigQuery e.g. - per minute billing, instant spin up of warehouse. Overall, the cost and time savings swayed us in favor of Snowflake.
Features
Alkira Network CloudGoogle BigQuerySnowflake
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Alkira Network Cloud
-
Ratings
Google BigQuery
8.4
79 Ratings
2% below category average
Snowflake
-
Ratings
Automatic software patching00 Ratings8.017 Ratings00 Ratings
Database scalability00 Ratings9.078 Ratings00 Ratings
Automated backups00 Ratings8.524 Ratings00 Ratings
Database security provisions00 Ratings8.772 Ratings00 Ratings
Monitoring and metrics00 Ratings8.274 Ratings00 Ratings
Automatic host deployment00 Ratings8.013 Ratings00 Ratings
Best Alternatives
Alkira Network CloudGoogle BigQuerySnowflake
Small Businesses
Google BigQuery
Google BigQuery
Score 8.7 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Google BigQuery
Google BigQuery
Score 8.7 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 8.7 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Google BigQuery
Google BigQuery
Score 8.7 out of 10
Enterprises
Snowflake
Snowflake
Score 8.7 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Google BigQuery
Google BigQuery
Score 8.7 out of 10
All AlternativesView all alternativesView all alternativesView all alternatives
User Ratings
Alkira Network CloudGoogle BigQuerySnowflake
Likelihood to Recommend
-
(0 ratings)
8.8
(78 ratings)
8.9
(43 ratings)
Likelihood to Renew
-
(0 ratings)
8.1
(5 ratings)
10.0
(2 ratings)
Usability
-
(0 ratings)
7.2
(6 ratings)
9.3
(19 ratings)
Availability
-
(0 ratings)
7.3
(1 ratings)
-
(0 ratings)
Performance
-
(0 ratings)
6.4
(1 ratings)
-
(0 ratings)
Support Rating
-
(0 ratings)
5.7
(11 ratings)
9.9
(8 ratings)
Configurability
-
(0 ratings)
6.4
(1 ratings)
-
(0 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
10.0
(1 ratings)
8.0
(1 ratings)
Ease of integration
-
(0 ratings)
7.3
(1 ratings)
-
(0 ratings)
Product Scalability
-
(0 ratings)
7.3
(1 ratings)
-
(0 ratings)
Professional Services
-
(0 ratings)
8.2
(2 ratings)
-
(0 ratings)
User Testimonials
Alkira Network CloudGoogle BigQuerySnowflake
Likelihood to Recommend
Alkira
No answers on this topic
Google
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
Read full review
Snowflake Computing
Snowflake is well suited when you have to store your data and you want easy scalability and increase or decrease the storage per your requirement. You can also control the computing cost, and if your computing cost is less than or equal to 10% of your storage cost, then you don't have to pay for computing, which makes it cost-effective as well.
Read full review
Pros
Alkira
No answers on this topic
Google
  • Realtime integration with Google Sheets.
  • GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
  • Seamless integration with other GCP products.
  • A simple pipeline might look like this:-
  • GForms -> GSheets -> BigQuery -> Looker
  • It all links up really well and with ease.
  • One instance holds many projects.
  • Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
Read full review
Snowflake Computing
  • Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
  • Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
  • Snowflake manages concurrency better in our trials than other premium competitors
  • Snowflake has little to no setup and ramp up time
  • Snowflake offers online training for various employee types
Read full review
Cons
Alkira
No answers on this topic
Google
  • Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
  • If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
  • It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
Read full review
Snowflake Computing
  • Add constraints for views and not just for tables
  • Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
Read full review
Likelihood to Renew
Alkira
No answers on this topic
Google
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
Snowflake Computing
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
Read full review
Usability
Alkira
No answers on this topic
Google
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
Read full review
Snowflake Computing
Because the fact that you can query tons of data in a few seconds is incredible, it also gives you a lot of functions to format and transform data right in your query, which is ideal when building data models in BI tools like Power BI, it is available as a connector in the most used BI tools worldwide.
Read full review
Reliability and Availability
Alkira
No answers on this topic
Google
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
Read full review
Snowflake Computing
No answers on this topic
Performance
Alkira
No answers on this topic
Google
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
Read full review
Snowflake Computing
No answers on this topic
Support Rating
Alkira
No answers on this topic
Google
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
Snowflake Computing
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
Read full review
Alternatives Considered
Alkira
No answers on this topic
Google
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
Read full review
Snowflake Computing
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
Read full review
Contract Terms and Pricing Model
Alkira
No answers on this topic
Google
None so far. Very satisfied with the transparency on contract terms and pricing model.
Read full review
Snowflake Computing
No answers on this topic
Scalability
Alkira
No answers on this topic
Google
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
Read full review
Snowflake Computing
No answers on this topic
Professional Services
Alkira
No answers on this topic
Google
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
Snowflake Computing
No answers on this topic
Return on Investment
Alkira
No answers on this topic
Google
  • Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
  • We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
  • Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
Read full review
Snowflake Computing
  • With separate compute and storage feature, the queries get executed quickly and it improves our overall productivity.
  • Earlier we were using a different product for analytical purposes, but with Snowflake's in-built analytical feature we are now able to save money.
  • Snowflake is cost efficient, features like auto suspend for compute resources helped to control the costs.
Read full review
ScreenShots

Google BigQuery Screenshots

Screenshot of Migrating data warehouses to BigQuery - Features a streamlined migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the fully managed BigQuery Migration Service.Screenshot of bringing any data into BigQuery - Data files can be uploaded from local sources, Google Drive, or Cloud Storage buckets, using BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, by replicating data from relational databases with Datastream for BigQuery, or by leveraging Google's data integration partnerships.Screenshot of generative AI use cases with BigQuery and Gemini models - Data pipelines that blend structured data, unstructured data and generative AI models together can be built to create a new class of analytical applications. BigQuery integrates with Gemini 1.0 Pro using Vertex AI. The Gemini 1.0 Pro model is designed for higher input/output scale and better result quality across a wide range of tasks like text summarization and sentiment analysis. It can be accessed using simple SQL statements or BigQuery’s embedded DataFrame API from right inside the BigQuery console.Screenshot of insights derived from images, documents, and audio files, combined with structured data - Unstructured data represents a large portion of untapped enterprise data. However, it can be challenging to interpret, making it difficult to extract meaningful insights from it. Leveraging the power of BigLake, users can derive insights from images, documents, and audio files using a broad range of AI models including Vertex AI’s vision, document processing, and speech-to-text APIs, open-source TensorFlow Hub models, or custom models.Screenshot of event-driven analysis - Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows users to make business decisions based on the freshest data. Or Dataflow can be used to enable simplified streaming data pipelines.Screenshot of predicting business outcomes AI/ML - Predictive analytics can be used to streamline operations, boost revenue, and mitigate risk. BigQuery ML democratizes the use of ML by empowering data analysts to build and run models using existing business intelligence tools and spreadsheets.

Snowflake Screenshots

Screenshot of Snowflake Installation