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Google BigQuery VS Stonebranch

Compare Google BigQuery VS Stonebranch and see what are their differences

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Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.

Stonebranch logo Stonebranch

Stonebranch builds IT orchestration and automation solutions that transform business IT environments from simple IT task automation into sophisticated, real-time business service automation.
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • Stonebranch Landing Page as of 10-30-24
    Landing Page as of 10-30-24 //
    2024-10-30
  • Stonebranch Drag-and-Drop Workflow
    Drag-and-Drop Workflow //
    2024-01-22
  • Stonebranch Integrated Dashboard
    Integrated Dashboard //
    2024-01-22

No matter the degree of automation, the Stonebranch platform is simple, modern, and secure. Using the Stonebranch Universal Automation Center, enterprises can seamlessly orchestrate workloads and data across technology ecosystems and silos. Headquartered in Atlanta, Georgia, with points of contact and support across the globe Stonebranch serves some of the world's largest financial, manufacturing, healthcare, travel, transportation, energy, and technology institutions. Learn more: www.stonebranch.com

Google BigQuery features and specs

  • Scalability
    BigQuery can effortlessly scale to handle large volumes of data due to its serverless architecture, thereby reducing the operational overhead of managing infrastructure.
  • Speed
    It leverages Google's infrastructure to provide high-speed data processing, making it possible to run complex queries on massive datasets in a matter of seconds.
  • Integrations
    BigQuery easily integrates with various Google Cloud Platform services, as well as other popular data tools like Looker, Tableau, and Power BI.
  • Automatic Optimization
    Features like automatic data partitioning and clustering help to optimize query performance without requiring manual tuning.
  • Security
    BigQuery provides robust security features including IAM roles, customer-managed encryption keys, and detailed audit logging.
  • Cost Efficiency
    The pricing model is based on the amount of data processed, which can be cost-effective for many use cases when compared to traditional data warehouses.
  • Managed Service
    Being fully managed, BigQuery takes care of database administration tasks such as scaling, backups, and patch management, allowing users to focus on their data and queries.

Possible disadvantages of Google BigQuery

  • Cost Predictability
    While the pay-per-use model can be cost-efficient, it can also make cost forecasting difficult. Unexpected large queries could lead to higher-than-anticipated costs.
  • Complexity
    The learning curve can be steep for those who are not already familiar with SQL or Google Cloud Platform, potentially requiring training and education.
  • Limited Updates
    BigQuery is optimized for read-heavy operations, and it can be less efficient for scenarios that require frequent updates or deletions of data.
  • Query Pricing
    Costs are based on the amount of data processed by each query, which may not be suitable for use cases that require frequent analysis of large datasets.
  • Data Transfer Costs
    While internal data movement within Google Cloud can be cost-effective, transferring data to or from other services or on-premises systems can incur additional costs.
  • Dependency on Google Cloud
    Organizations heavily invested in multi-cloud or hybrid-cloud strategies may find the dependency on Google Cloud limiting.
  • Cold Data Performance
    Query performance might be slower for so-called 'cold data,' or data that has not been queried recently, affecting the responsiveness for some workloads.

Stonebranch features and specs

  • Workload Automation
    Job scheduling and Workload Automation capabilities that support on-prem, cloud and containerized microservices in a hybrid IT enviornment.
  • Data Pipeline Orchestration
    Simplify the management of your data pipeline with a centralized orchestration solution built to keep data moving—so that insights are delivered to the business without error.
  • Cloud Automation
    Centralize the management of automated workloads across private cloud, public cloud, and multi-cloud environment.
  • Managed File Transfer
    Move data between any type of cloud, on-prem or containerized system.
  • DevOps and DataOps Enabled
    Support dev, test, prod processes within the platorm, or by connecting to third party repositories like GitHub.
  • SaaS
    Deployment options include both SaaS and on-premises.

Analysis of Google BigQuery

Overall verdict

  • Google BigQuery is a powerful and flexible data warehouse solution that suits a wide range of data analytics needs. Its ability to handle large volumes of data quickly makes it a preferred choice for organizations looking to leverage their data effectively.

Why this product is good

  • Google BigQuery is a fully-managed data warehouse that simplifies the analysis of large datasets. It is known for its scalability, speed, and integration with other Google Cloud services. It supports standard SQL, has built-in machine learning capabilities, and allows for seamless data integration from various sources. The serverless architecture means that users don't need to worry about infrastructure management, and its pay-as-you-go model provides cost efficiency.

Recommended for

  • Businesses requiring fast processing of large datasets
  • Organizations that already utilize Google Cloud services
  • Companies looking for a cost-effective, scalable analytics solution
  • Teams interested in using SQL for data analysis
  • Data scientists integrating machine learning with their data workflows

Analysis of Stonebranch

Overall verdict

  • Yes, Stonebranch is generally considered a good option for organizations seeking robust IT automation solutions. Its combination of powerful features, flexibility, and positive user reviews highlight its effectiveness in the industry.

Why this product is good

  • Stonebranch is a reputable provider specializing in IT automation and orchestration solutions. The company is known for its innovative platform that enables organizations to automate and integrate business processes, improving efficiencies and reducing manual errors. Their solutions are highly scalable, adaptable to various industries, and come with strong customer support. Additionally, Stonebranch has received positive feedback for its user-friendly interface and comprehensive feature set which include workload automation, managed file transfer, and cloud service automation.

Recommended for

    Stonebranch is recommended for medium to large enterprises looking for reliable and scalable IT automation tools. It is especially suitable for organizations that require seamless integration across diverse IT environments and those looking to optimize their IT operations by reducing manual intervention and errors.

Google BigQuery videos

+ Add

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Stonebranch videos

+ Add

Stonebranch's Service Orchestration and Automation Platform (SOAP)

More videos:

  • Review - About the Stonebranch Universal Automation Center Platform

Category Popularity

0-100% (relative to Google BigQuery and Stonebranch)

Google BigQuery

Stonebranch

Data Dashboard
100 100%
Data Dashboard
0% 0
IT Automation
0 0%
IT Automation
100% 100
Big Data
100 100%
Big Data
0% 0
Workflow Automation
0 0%
Workflow Automation
100% 100

User comments

Share your experience with using Google BigQuery and Stonebranch. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google BigQuery and Stonebranch

Google BigQuery Reviews

Data Warehouse Tools
Google BigQuery: Similar to Snowflake, BigQuery offers a pay-per-use model with separate charges for storage and queries. Storage costs start around $0.01 per GB per month, while on-demand queries are billed at $5 per TB processed.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
You can also use BigQuery’s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or “heavy” queries that operate using a large set of data. This means it’s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Source: www.shipyardapp.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io
16 Top Big Data Analytics Tools You Should Know About
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.
Source: www.analytixlabs.co.in

Stonebranch Reviews

Top 10 Control-M Alternatives in ’23
However, choosing a workload automation solution that fits your business goals and objectives in a complex market landscape can be challenging. For instance, Control-M is one of the WLA market leaders along with ActiveBatch, Redwood RunMyJobs, Stonebranch Universal Automation Center (UAC) and JAMS WLA according to AIMultiple’s analysis based on 7 different data sources.
Source: research.aimultiple.com
9 Control-M Alternatives & Competitors In 2023
Stonebranch helps organizations of any size scale and complexity scale up or down as needed. In addition to providing scalable IT automation, Stonebranch simplifies complex IT environments with its platform-agnostic, cloud-based architecture. Customers can benefit from a smoother transition to the cloud without sacrificing security, flexibility, or data security. Regardless...
Source: www.softwaretestingmaterial.com
The Top 5 BMC Control-M API Alternatives
With Stonebranch, organizations can centrally manage and automate complex business processes across on-premises, cloud, and hybrid environments. UAC is designed to simplify IT automation and make it more accessible to business users while still providing advanced features for IT operations teams.
Source: www.redwood.com

Social recommendations and mentions

Based on our record, Google BigQuery seems to be more popular. It has been mentiond 42 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google BigQuery mentions (42)

  • Every Database Will Support Iceberg — Here's Why
    This isn’t hypothetical. It’s already happening. Snowflake supports reading and writing Iceberg. Databricks added Iceberg interoperability via Unity Catalog. Redshift and BigQuery are working toward it. - Source: dev.to / about 1 month ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Many of these companies first tried achieving real-time results with batch systems like Snowflake or BigQuery. But they quickly found that even five-minute batch intervals weren't fast enough for today's event-driven needs. They turn to RisingWave for its simplicity, low operational burden, and easy integration with their existing PostgreSQL-based infrastructure. - Source: dev.to / about 1 month ago
  • How to Pitch Your Boss to Adopt Apache Iceberg?
    If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, you’ve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming — one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / about 2 months ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 4 months ago
  • Docker vs. Kubernetes: Which Is Right for Your DevOps Pipeline?
    Pro Tip: Use Kubernetes operators to extend its functionality for specific cloud services like AWS RDS or GCP BigQuery. - Source: dev.to / 7 months ago
View more

Stonebranch mentions (0)

We have not tracked any mentions of Stonebranch yet. Tracking of Stonebranch recommendations started around Mar 2021.

What are some alternatives?

When comparing Google BigQuery and Stonebranch, you can also consider the following products

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

ActiveBatch - Orchestrate the entire tech stack with ActiveBatch Workload Automation & Job Scheduling. Build and manage workflows from one place.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Control-M - Control‑M simplifies and automates diverse batch application workloads while reducing failure rates, improving SLAs, and accelerating application deployment.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

JAMS Scheduler - Enterprise workload automation software supporting processes on Windows, Linux, UNIX, iSeries, SAP, Oracle, SQL, ERPs and more.

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