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Google BigQuery VS Synapse

Compare Google BigQuery VS Synapse and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Google BigQuery logo Google BigQuery

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

Synapse logo Synapse

Synapse is a semantic launcher written in Vala that you can use to start applications as well as find and access relevant documents and files by making use of the Zeitgeist engine.
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • Synapse Landing page
    Landing page //
    2023-09-17

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.

Synapse features and specs

  • Open Source
    Synapse is an open-source project, which means that it is free to use, modify, and distribute. This allows for community contributions and transparency in development.
  • Lightweight
    Synapse is designed to be lightweight and fast, which ensures that it does not consume excessive system resources, making it suitable for a wide range of hardware configurations.
  • Customizable
    Users can customize Synapse through plugins and scripts, allowing for personalized workflows and extended functionality tailored to individual needs.
  • Cross-Platform
    Synapse is cross-platform and can be used on various operating systems, providing flexibility and consistency for users who work in multi-OS environments.
  • Efficient Search
    Synapse offers efficient search capabilities, allowing users to quickly find and launch applications, files, and perform other tasks through a convenient interface.

Possible disadvantages of Synapse

  • Learning Curve
    New users may find it difficult to familiarize themselves with Synapse's features and customization options, leading to an initial learning curve.
  • Limited Documentation
    Although active, Synapse's documentation can be somewhat limited or fragmented, making it difficult for some users to find comprehensive guides and support.
  • Occasional Bugs
    As with many open-source projects, users may encounter occasional bugs or stability issues, which can affect the user experience until they are resolved.
  • Community Dependency
    Development and support largely depend on community contributions and volunteers, which can lead to slower resolution of issues and less predictable updates.
  • Less Integration
    Compared to some proprietary alternatives, Synapse may offer fewer integration options with other applications and services, limiting its functionality for some users.

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 Synapse

Overall verdict

  • Synapse is a well-regarded application among Linux users due to its speed and functionality. It is considered a good choice if you are seeking a fast, lightweight, and extensible application launcher.

Why this product is good

  • Synapse, available on launchpad.net, is a semantic launcher for Linux. It is favored for its simplicity and efficiency in launching applications, finding files, and executing commands. Synapse enhances productivity by using plugins to quickly locate and open items on your system without needing to navigate menus or folders manually. Its lightweight design ensures minimal system resource usage, making it a good tool for older hardware as well.

Recommended for

    Synapse is particularly recommended for Linux users who value speed and efficiency in workflow management. It is an excellent choice for those running older systems or anyone looking to simplify their desktop environment by reducing the time spent navigating through traditional application menus.

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

Synapse videos

+ Add

Cannondale Synapse Hi-Mod Disc Red eTap | Review | Cycling Weekly

More videos:

  • Review - Cannondale Synapse Review - Endurance Road Bike
  • Review - CANNONDALE SYNAPSE REVIEW (AFTER 9 MONTHS!)

Category Popularity

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

Google BigQuery

Synapse

Data Dashboard
100 100%
Data Dashboard
0% 0
App Launcher
0 0%
App Launcher
100% 100
Big Data
100 100%
Big Data
0% 0
Windows Tools
0 0%
Windows Tools
100% 100

User comments

Share your experience with using Google BigQuery and Synapse. 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 Synapse

Google BigQuery Reviews

Database for Data Analytics
Processing typeDescriptionUse casesCommon databasesProcessing typesProcesses data in scheduled intervals (hours, days). High-latency but cost-efficient for large datasets.Financial reporting, trend analysis, historical analyticsSnowflake, Amazon Redshift, Google BigQueryContinuously ingests and processes data with minimal latency for real-time decision-making.Fraud...
Source: blog.devart.com
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 BigQueryโ€™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 โ€œheavyโ€ queries that operate using a large set of data. This means itโ€™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

Synapse Reviews

Top Big Data Tools For 2021
Azure is a cloud computing platform that serves as a basis for many data solutions. As explained previously in another post on this blog, Synapse Analytics is a rebranded version of the Azure SQL Data Warehouse. Among the improvements included in the new version, it is worth noting that now it integrates with Apache Spark and makes it possible to combine data warehousing and...
Source: blog.bismart.com

Social recommendations and mentions

Based on our record, Google BigQuery seems to be a lot more popular than Synapse. While we know about 47 links to Google BigQuery, we've tracked only 1 mention of Synapse. 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 (47)

  • Ruby on Rails Performance: 7 Lessons from Scaling FirstPromoter
    We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ€” we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 4 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 5 months ago
  • What if ML pipelines had a lock file?
    Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 6 months ago
  • Best SQL Courses with Certificates for 2026
    SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโ€”while dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 8 months ago
  • Why Your Snowflake Bill is High and How to Fix It with a Hybrid Approach
    Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 9 months ago
View more

Synapse mentions (1)

  • Opportunistic, pragmatic Pop!
    Ditch Cosmic's launcher. It is underpowered. The best launcher to this day is still Synapse, even though it is not in active development anymore. It still has great potential and could easily be extended to really fit into Pop while providing some new functions nothing else has. Source: over 4 years ago

What are some alternatives?

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

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

DockbarX - DockbarX is a standalone dock that groups and launches applications.

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

Gnome Do - Simple, sleek, swift, smart. Do. GNOME Do allows you to quickly search for many items present on your desktop or the web, and perform useful actions on those items. GNOME Do is inspired by Quicksilver & GNOME Launch Box.

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.

Gnome-Pie - Gnome-Pie is a circular application launcher for Linux.

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