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Splid VS Google BigQuery

Compare Splid VS Google BigQuery and see what are their differences

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

Splid logo Splid

Splid helps friends manage their money.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Splid Landing page
    Landing page //
    2018-09-30
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Splid features and specs

  • User-Friendly Interface
    Splid offers an intuitive and easy-to-use interface that makes it simple for users to split expenses without any confusion.
  • Offline Functionality
    Users can log expenses and use the app even without an internet connection, which is useful in remote areas.
  • Multiple Currency Support
    Splid allows users to add expenses in different currencies, making it convenient for international travel and expenses.
  • No Sign-Up Required
    The app does not require users to create an account, simplifying access and reducing privacy concerns.
  • Easy Sharing
    Users can easily share expense reports with group members via a link, simplifying communication and transparency.

Possible disadvantages of Splid

  • Limited Integration
    Splid lacks integration with other financial apps or services, which can limit its functionality for some users.
  • Manual Expense Entry
    All expenses must be entered manually, which can be time-consuming compared to apps that offer receipt scanning.
  • No Real-Time Sync
    Changes are not updated in real-time across devices, potentially leading to discrepancies if multiple users are managing a list.
  • Basic Features Free
    While the basic app is free, advanced features require a paid upgrade, which might not be ideal for all users.
  • Limited to Group Expense
    Splid is focused on group expense sharing, lacking features for individual finance management or budgeting.

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.

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

Splid videos

+ Add

"Splid" by Kvelertak (ALBUM OF THE YEAR CONTENDER?) | ALBUM REVIEW

More videos:

  • Review - Album Review/Reaction: Kvelertak - Splid
  • Review - Kvelertak: Splid -- 💿 album review 💿

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

Category Popularity

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

Splid

Google BigQuery

Personal Finance
100 100%
Personal Finance
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Bill-Splitting Apps
100 100%
Bill-Splitting Apps
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Splid and Google BigQuery. 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 Splid and Google BigQuery

Splid Reviews

  1. dee parkes
    · retired at retired ·
    great! easy to use, versatile, flexible. Recommended.

    I prefer this app to similar ones I've tried. It seems clearer, more straightforward and simpler to use for normal holidays etc. But if you need more complex arrangements it's versatile too: in that you can have multiple currencies; and groups containing different people.

12 Best Bill Splitting Apps in 2023
Splid is an excellent app for those who want to take their bill splitting to the next level. It is among the popular bill splitting apps that supports advanced features like location-based payment suggestions, detailed accounts of shared expenses, and a user-friendly interface, Splid app makes splitting bills easier than ever before.
Source: www.mobileappdaily.com
Best Bill-Splitting Apps
Splitting up the cost of group trips can be tough. Splid allows you to add in all the expenses of a trip and then split it up among each person on the trip. The app is useful for splitting up non-trip expenses as well. Multiple payees can be added to each expense, for example, if two people covered the cost of groceries upfront, but five people need to chip in on the bill....
Source: www.thebalancemoney.com

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 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

Social recommendations and mentions

Based on our record, Google BigQuery seems to be a lot more popular than Splid. While we know about 47 links to Google BigQuery, we've tracked only 2 mentions of Splid. 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.

Splid mentions (2)

  • Running an Open Source App: Usage, Costs and Community Donations
    Would be interesting to see how this compares to https://splid.app/. - Source: Hacker News / almost 2 years ago
  • Show HN: An alternative to Splitwise, more minimalist, no ads, no account
    Https://splid.app/ is a great no-account alternative. - Source: Hacker News / about 4 years ago

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 — 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 / 5 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 / 6 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 / 7 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 transferability—while dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 9 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 / 10 months ago
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What are some alternatives?

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

Splitwise - Splitwise is a free tool for friends and roommates to track bills and other shared expenses, so that everyone gets paid back. On the web, iPhone, and Android!

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

Tricount - Manage and share expenses with friends

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.

Settle Up - SETTLE UP is an indispensable app for friends and flatmates who need to keep track of shared bills...

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.

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