BigQuery vs 1010data

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Our analysts compared BigQuery vs 1010data based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

1010data Software Tool

Product Basics

BigQuery, a cloud-based data warehouse offered by Google, provides businesses with a scalable and cost-effective solution for analyzing massive datasets. It eliminates the need for infrastructure management, allowing users to focus on extracting valuable insights from their data using familiar SQL and built-in machine learning capabilities. BigQuery's serverless architecture enables efficient scaling, allowing you to query terabytes of data in seconds and petabytes in minutes.

BigQuery is particularly well-suited for organizations dealing with large and complex datasets that require rapid analysis. Its ability to integrate data from various sources, including Google Cloud Platform and other cloud providers, makes it a versatile tool for businesses with diverse data landscapes. Key benefits include scalability, ease of use, and cost-effectiveness. BigQuery offers a pay-as-you-go pricing model, allowing you to only pay for the resources you consume. You are billed based on the amount of data processed by your queries and the amount of data stored.

While BigQuery offers numerous advantages, it's important to consider factors such as your specific data analytics needs and budget when comparing it to similar products. User experiences with BigQuery have generally been positive, highlighting its speed, scalability, and ease of use. However, some users have noted that the pricing structure can become complex for highly demanding workloads.

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1010data is a market intelligence and enterprise analytics solution that helps track consumer insights and market trends. In addition to vendor-critical insights, it provides brand performance metrics to buy-side entities. Seamlessly embeddable, it can also function as a standalone private-label option. Data scientists and statisticians leverage its integration with R to view and query data tables.

It enables analytics development through its QuickApps framework. By tracking consumer spending trends and brand performance, it enables businesses to better position their products in the marketplace.
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$6.25/TiB, Usage-Based
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$12,000/User, Annually
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Product Insights

  • Forecast and Plan Ahead: Ingest large amounts of data quickly to strengthen forecasting and boost decision-making processes. 
  • Deliver Insights: Find discrepancies in data and act on them accordingly. 
  • Focus on Analytics and Not Infrastructure: Handles large volumes of data without putting strain on an organization’s IT resources. 
  • Provide a User-Friendly Environment: It’s user-friendly for both technical and non-technical users. High-level knowledge is not necessary to operate the software effectively. 
  • Speed Up Processes: Utilizes fast SQL databases to quickly and efficiently analyze terabytes worth of data. 
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  • Track Consumer Trends:  Discover how consumers search for and assess products before buying. Identify product affinities by segments and add value through basket analysis to expand the category assortment. Analyze customers based on geography and spending tiers to create targeted marketing strategies. 
  • Analyze Buyer Behavior:  Drive customer retention and higher loyalty by analyzing shopper lifecycles by retailer with geographical drill-down capabilities. Track the path-to-purchase customer experience and the buyer acquisition process. Monitor points of purchase — whether in-store or online, which stores were visited pre-purchase and the items considered before buying. 
  • Maximize ROI:  Assess shopping behavior at the category, brand, merchant and product levels. Analyze conversion rates and key metrics’ progression over time by new, lost and retained customers. Uncover churn rate figures by segment and spending capacity to drive remedial strategies. 
  • Track the Competition:  Track the product’s market position across hundreds of consumer goods categories. Identify disruptors from other brands on the market. Justify specific product category positioning with data on emerging competitors. Analyze merchandising strategies and promotional spend across merchants. 
  • Application Development:  Create end-to-end analytic applications directly atop proprietary granular data through its QuickApps framework and iterate when needed. Deploy them via desktop web, mobile devices or external applications with legacy governance parameters. 
  • Buy-Side Insights:  Inform buy-side investment decisions by tracking consumer spending, transactions and basket size of multiple brands. Analyze company performance by quarter, month, week and day. Get granular insights on sector trends, customer segments or geospatial consumer data, refreshed daily. 
  • Data Security:  Secure by design, it has a stateful architecture for privately allocated, separate user sessions. It is HIPAA compliant and SOC 2 Type II certified, with support for single sign-on via SAML 2.0 authentication. 
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  • Machine Learning: Comes with machine learning modules that can perform mass-segmentation and recommendations in seconds. These modules can be built and trained within minutes without ingesting data for training. 
  • Cloud Hosted: Handles all the hardware provisioning, warehousing and hardware management from the cloud. 
  • Real-Time Analytics: Large volumes of business data are quickly analyzed and presented to the user to ensure that insights and data discrepancies can be immediately uncovered. 
  • Automated Backups: Data is automatically stored and backed up multiple times a day. Data histories can be easily restored to prevent loss and major changes. 
  • Big Data Ecosystem Integrations: Integrate with other big data products such as Hadoop, Spark and Beam. Data can be directly written from the system into these products. 
  • Data Governance: Features such as access management, filter views, encryption and more are included in the software. The product is compliant with data regulations such as the GDPR. 
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  • Cloud-Native: Built from the ground up to enable large-scale, multi-party data sharing and analytics in the cloud. 
  • Advanced Analytics: Derive meaningful data insights by creating advanced data models against complex data sets. Perform time-series analysis, statistical functions and machine learning through its functions library. 
  • Visualizations: Create charts, graphs, heat maps and more through its rich functions library and a visual expression builder. Leverage the power of analytics through integration with visualization tools like Tableau, Logi Analytics, Information Builders and Metric Insights. 
  • Reporting: Acquire business-critical insights through standardized reporting, consistent KPI monitoring and guided ad-hoc reporting. Gain confidence in data with full visibility into proprietary information and calculation lineage. Save data results locally or to a file system via FTP, or in a data table. Or, export it in CSV, PDF or Excel format. 
  • Data Management: Pull and blend disparate, complex data sets on-the-fly into an analysis-ready format. Assign role-based permissions for access to tables, rows and columns. Tracks usage activity through audit trails and logs that include the account information, IP address and tables accessed. 
  • Integrations: Run advanced data analytics via the R console through R1010. Easily access data tables and view them in Tableau with real-time integration, data discovery and SQL support. Create spreadsheets that access the 1010 data platform via its Excel add-in. 
  • Universal Calculation Library: Quickly answer data-based queries by analyzing complex datasets through centralized and standardized calculations. 
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Product Ranking

#10

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Big Data Analytics Tools

#44

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Big Data Analytics Tools

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User Sentiment Summary

Excellent User Sentiment 724 reviews
Good User Sentiment 25 reviews
90%
of users recommend this product

BigQuery has a 'excellent' User Satisfaction Rating of 90% when considering 724 user reviews from 3 recognized software review sites.

78%
of users recommend this product

1010data has a 'good' User Satisfaction Rating of 78% when considering 25 user reviews from 2 recognized software review sites.

4.4 (292)
n/a
4.6 (283)
4.0 (18)
4.4 (149)
3.7 (7)

Awards

BigQuery stands above the rest by achieving an ‘Excellent’ rating as a User Favorite.

User Favorite Award

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Synopsis of User Ratings and Reviews

Performance: The system can execute queries on massive amounts of data with agility, as specified by about 89% of users who mentioned performance.
Functionality: About 68% of users who reviewed functionality talked about its robust inbuilt features.
Ease of Use: The UI is simple and easy to navigate, according to about 72% of users who talked about user-friendliness.
Integration: Approximately 75% of reviewers who talked about integration said that it connects to numerous other tools seamlessly.
Scalability: All users who reviewed scalability said that the platform scales to thousands of servers.
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Robust Data Processing: Handles large volumes of structured and unstructured data efficiently, enabling comprehensive data analysis.
Scalable Architecture: Supports growing data volumes and user demands, ensuring seamless performance as your business expands.
Advanced Analytics Capabilities: Provides sophisticated machine learning algorithms and statistical techniques for in-depth data exploration and predictive modeling.
User-Friendly Interface: Intuitive dashboards and visualization tools simplify data analysis, making it accessible to users of all technical levels.
Data Security and Compliance: Adheres to industry standards and regulations, ensuring the protection and privacy of sensitive data.
Cost-Effective Solution: Offers flexible pricing models and cloud-based deployment options, reducing upfront investment and ongoing maintenance costs.
Excellent Customer Support: Provides dedicated technical support and documentation, ensuring smooth implementation and ongoing assistance.
Community and Resources: Fosters a vibrant user community and offers extensive resources, including tutorials, webinars, and case studies.
Integrations with Other Tools: Seamlessly connects with popular business intelligence and data visualization tools, enhancing data analysis capabilities.
Proven Track Record: Trusted by numerous businesses and organizations, delivering successful data-driven initiatives.
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Cost: Approximately 76% of users who mentioned cost complained that it’s expensive, and charges can rack up quickly if queries aren’t properly constructed.
Learning Curve: About 82% of users mentioned that the software has a steep learning curve.
Resources: About 89% of users who spoke about resources said that documentation and video tutorials are lacking and need improvement.
Visualization: Data visualization capabilities aren’t up to the mark, according to all users who talked about visualization.
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Complexity: Challenging to use for non-technical users, requiring specialized knowledge and skills.
Limited Customization: Pre-defined templates and limited flexibility, hindering the adaptation to specific business needs.
Data Quality Issues: Inconsistent data quality and lack of data validation tools, leading to unreliable insights.
Scalability Challenges: Struggles to handle large and complex datasets, resulting in performance issues and delayed analysis.
Vendor Lock-in: Proprietary technologies and limited data portability, restricting users from switching to alternative solutions.
Costly Licensing: Expensive licensing fees and hidden costs, making it unaffordable for some organizations.
Lack of Real-time Analysis: Inability to process and analyze data in real-time, hindering timely decision-making.
Insufficient Support: Limited technical support and documentation, leaving users struggling with implementation and troubleshooting.
Privacy Concerns: Concerns about data privacy and security, as tools often require access to sensitive information.
Steep Learning Curve: Extensive training and time investment required to master the tools, hindering adoption.
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Bigquery is a scalable big data warehouse solution. It enables users to pull correlated data streams using SQL like queries. Queries are executed fast regardless of the size of the datasets. It manages the dynamic distribution of workloads across computational clusters. The easy-to-navigate UI is robust and allows the user to create and execute machine learning models seamlessly. Users liked that it can connect to a variety of data analytics and visualization tools. However, users complained that query optimization is an additional hassle they have to deal with, as the solution is expensive and poorly constructed queries can quickly accumulate charges. It can be overwhelming for the non-technical user, and SQL coding knowledge is required to leverage its data analysis capabilities. Data visualization features are lacking and in need of improvement.

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1010data's user reviews over the past year paint a picture of a robust big data analytics tool with strengths in data visualization, ease of use, and customer support. Users have praised its intuitive interface, which allows even non-technical users to quickly create and share insights. Additionally, the tool's advanced visualization capabilities, such as interactive dashboards and customizable charts, have been highlighted as key differentiators, enabling users to explore and present data in a visually appealing and impactful manner. However, some users have expressed concerns regarding the tool's scalability and performance when handling extremely large datasets. Additionally, the lack of certain advanced features, such as real-time analytics and predictive modeling, has been noted as a weakness compared to more comprehensive analytics platforms. Nonetheless, 1010data remains a popular choice for businesses seeking a user-friendly and visually oriented tool for their data analytics needs, particularly for those with smaller to mid-sized datasets.

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