Google BigQuery vs. Microsoft Dynamics GP

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google BigQuery
Score 8.8 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)
Microsoft Dynamics GP
Score 5.1 out of 10
N/A
Microsoft Dynamics GP is an ERP software with accounting capabilities. It includes various packs for customizability and features tailored to specific industries’ needs. GP is offered as a perpetual license or subscription.N/A
Pricing
Google BigQueryMicrosoft Dynamics GP
Editions & Modules
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
Google BigQueryMicrosoft Dynamics GP
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Google BigQueryMicrosoft Dynamics GP
Features
Google BigQueryMicrosoft Dynamics GP
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google BigQuery
8.5
80 Ratings
0% above category average
Microsoft Dynamics GP
-
Ratings
Automatic software patching8.017 Ratings00 Ratings
Database scalability9.179 Ratings00 Ratings
Automated backups8.524 Ratings00 Ratings
Database security provisions8.773 Ratings00 Ratings
Monitoring and metrics8.475 Ratings00 Ratings
Automatic host deployment8.013 Ratings00 Ratings
Payroll Management
Comparison of Payroll Management features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
6.4
20 Ratings
17% below category average
Pay calculation00 Ratings6.319 Ratings
Benefit plan administration00 Ratings5.915 Ratings
Direct deposit files00 Ratings7.518 Ratings
Salary revision and increment management00 Ratings6.517 Ratings
Reimbursement management00 Ratings6.016 Ratings
Customization
Comparison of Customization features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
4.3
27 Ratings
55% below category average
API for custom integration00 Ratings2.526 Ratings
Plug-ins00 Ratings6.021 Ratings
Security
Comparison of Security features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
7.0
40 Ratings
16% below category average
Single sign-on capability00 Ratings5.932 Ratings
Role-based user permissions00 Ratings8.240 Ratings
Reporting & Analytics
Comparison of Reporting & Analytics features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
5.4
41 Ratings
37% below category average
Dashboards00 Ratings3.529 Ratings
Standard reports00 Ratings6.239 Ratings
Custom reports00 Ratings6.539 Ratings
General Ledger and Configurable Accounting
Comparison of General Ledger and Configurable Accounting features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
5.1
48 Ratings
40% below category average
Accounts payable00 Ratings6.445 Ratings
Accounts receivable00 Ratings5.936 Ratings
Cash management00 Ratings6.436 Ratings
Bank reconciliation00 Ratings5.741 Ratings
Expense management00 Ratings4.531 Ratings
Time tracking00 Ratings8.014 Ratings
Fixed asset management00 Ratings4.628 Ratings
Multi-currency support00 Ratings2.919 Ratings
Multi-division support00 Ratings3.026 Ratings
Regulations compliance00 Ratings3.314 Ratings
Electronic tax filing00 Ratings9.012 Ratings
Self-service portal00 Ratings7.012 Ratings
Global Financial Support00 Ratings6.07 Ratings
Primary and Secondary Ledgers00 Ratings4.721 Ratings
Intercompany Accounting00 Ratings3.918 Ratings
Localizations00 Ratings4.513 Ratings
Journals and Reconciliations00 Ratings4.726 Ratings
Enterprise Accounting00 Ratings2.916 Ratings
Configurable Accounting00 Ratings4.117 Ratings
Centralized Rules Framework00 Ratings3.814 Ratings
Standardized Processes00 Ratings6.219 Ratings
Inventory Management
Comparison of Inventory Management features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
4.6
26 Ratings
46% below category average
Inventory tracking00 Ratings6.224 Ratings
Automatic reordering00 Ratings1.013 Ratings
Location management00 Ratings4.018 Ratings
Manufacturing module00 Ratings4.615 Ratings
Order Management
Comparison of Order Management features of Product A and Product B
Google BigQuery
-
Ratings
Microsoft Dynamics GP
3.7
25 Ratings
68% below category average
Pricing00 Ratings3.618 Ratings
Order entry00 Ratings3.621 Ratings
Credit card processing00 Ratings1.012 Ratings
Cost of goods sold00 Ratings5.225 Ratings
Order Orchestration00 Ratings5.39 Ratings
End-to-end order visibility00 Ratings3.812 Ratings
Order exception Resolution00 Ratings3.57 Ratings
Best Alternatives
Google BigQueryMicrosoft Dynamics GP
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
QuickBooks Self-Employed (discontinued)
QuickBooks Self-Employed (discontinued)
Score 6.2 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Zoho Books
Zoho Books
Score 9.1 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SAP Cloud ERP
SAP Cloud ERP
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google BigQueryMicrosoft Dynamics GP
Likelihood to Recommend
8.8
(77 ratings)
6.0
(51 ratings)
Likelihood to Renew
8.1
(5 ratings)
9.9
(7 ratings)
Usability
7.0
(6 ratings)
6.0
(7 ratings)
Availability
7.3
(1 ratings)
10.0
(2 ratings)
Performance
6.4
(1 ratings)
7.0
(1 ratings)
Support Rating
5.3
(11 ratings)
7.0
(5 ratings)
Implementation Rating
-
(0 ratings)
8.2
(3 ratings)
Configurability
6.4
(1 ratings)
-
(0 ratings)
Contract Terms and Pricing Model
10.0
(1 ratings)
-
(0 ratings)
Ease of integration
7.3
(1 ratings)
-
(0 ratings)
Product Scalability
7.3
(1 ratings)
9.1
(1 ratings)
Professional Services
8.2
(2 ratings)
-
(0 ratings)
User Testimonials
Google BigQueryMicrosoft Dynamics GP
Likelihood to Recommend
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
Microsoft
Microsoft Dynamics GP is well-suited for our environment, as we pay a diverse group of employees, including on-the-road drivers, shop employees (some in other locations), and office employees. It easily tracks time off, taxes, pay, etc. The reporting allows us to verify with our drivers how they are paid each week, whether it be through mileage or stop-offs.
Read full review
Pros
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
Microsoft
  • Great Plains started as back office/accounting, and that is still it's strong suit.
  • SQL and the GP programming language, Dexterity, provide a robust, scalable, and stable platform with well documented maintenance and repair procedures. Relatively easy to manage, tune, and support.
  • Microsoft support for GP verges on "particularly well". Doesn't quite get there but good enough once you know what you're doing
  • Strong partner network, including the GP User Group (GPUG)
Read full review
Cons
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
Microsoft
  • With respect to the allocations, once the expense is entered into the allocation account, you lose the ability to run any detail on just the total of the expense. It would be nice if you could run a trial balance on the allocation accounts the same way you can with regular accounts.
  • I've always thought security set up could be a bit simpler. It actually has gotten better through the years. Specifically, with eight separate entities, it would be nice to have a "master" setup where you could call up one group entity, assign the users rights, and then be finished. Currently, whenever I have a new user, I have to call up each individual entity and select all of the features I want the user to have. That means I have to do eight steps for each user.
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Likelihood to Renew
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
Microsoft
Due the economic challenges that Puerto Rico is having, the company has had to merge some companies in order to be more efficient. It has been easy in GP to process those merges, even thought we had to spend days to accomplish that the process was smooth and accurate. In addition we were able to streamline the purchasing and sales process and the organization is confident to keep renewing GP for the future versions.
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Usability
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
Microsoft
Though it is a basic accounting package, I believe some users do not find the old style menus and navigation options intuitive. There is also a great lack of training resources in the market, so users have to learn the product without guidance a lot, resulting in inefficient workflows and misuse or misunderstanding of many features.
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Reliability and Availability
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.
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Microsoft
No answers on this topic
Performance
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
Microsoft
No answers on this topic
Support Rating
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.
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Microsoft
The rating is directed to the thrid party serive provider that we use. I do not now how good the Microsoft direct support is.
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Implementation Rating
Google
No answers on this topic
Microsoft
Basically the challenge with this implementation was the Business Portal, too many errors and even the aplication is up and running the users are still having issues. We will start planning the migraton to GP 2015 soon.
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Alternatives Considered
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
Microsoft
I come from a strong background of using SAP. SAP doesn't have the flexibility of GP, an example would be SAP doesn't allow core mods, if they catch you, you lose support. Microsoft doesn't really care about mods, but they will be quick to have the vendor you used support your issue if it is caused by those mods. With SAP your company adapts to the software, where with GP you adapt the software to you.
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Contract Terms and Pricing Model
Google
None so far. Very satisfied with the transparency on contract terms and pricing model.
Read full review
Microsoft
No answers on this topic
Scalability
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.
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Microsoft
The functionality that GP and related ISV solutions offer and the ease of integration of GP to other systems makes it an extremely scalable solution
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Professional Services
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.
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Microsoft
No answers on this topic
Return on Investment
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.
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Microsoft
  • Microsoft Dynamics GP allows my clients to move from a paper or spreadsheet based company to an integrated, electronic, streamlined business. I love being able to help clients gain efficiencies through the use of Microsoft Dynamics GP.
  • Microsoft Dynamics GP allows for better customer service because everything is at our fingertips. If someone calls questioning an invoice, we can easily look it up. If someone calls stating they paid an invoice with a certain check number, we can quickly run a query to find that particular check number to see where it was applied.
  • Having everything on a single platform provides ease of use for upgrades, backups and end user training. There is only one software to learn!
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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.