Sold by: SparkLabs
Deployed on AWS
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SparkGrid simplifies database usage through a spreadsheet-like interface that empowers users to perform complex data management tasks on any Snowflake, MySQL, MariaDB, PostgreSQL, or Microsoft SQL Server database without the need for extensive technical expertise.
Overview
SparkGrid simplifies database usage through a spreadsheet-like interface that empowers users to perform complex data management tasks on any Snowflake, MySQL, MariaDB, PostgreSQL, or SQL Server database without the need for extensive technical expertise.
SparkGrid's tabularized GUI offers a seamless transition between intuitive visual displays and SQL queries, enabling users to navigate, select, and manipulate data effortlessly. Unlike traditional data management systems that may require specialized training, SparkGrid prioritizes accessibility, allowing users to add, remove, and edit rows, columns, and tables with ease.
This spreadsheet capability is only one aspect of SparkGrid. The software also allows users to enter a visualization of their database hierarchy, and provides options to rename, comment on, move, or delete database tables in addition to opening them as spreadsheets. Another view can convert small CSV files into full tables. Advanced users can take advantage of another tool it offers to view and edit columns in detail, including changing any column's data type, maximum length, and similar metadata. Upon changing a column's data type, SparkGrid will attempt to convert any incompatible cells and will inform the user if any incompatible cells remain after.
By encouraging direct database interaction and streamlining data management processes, SparkGrid empowers users to make informed decisions and drive innovation within their organizations.
As of this writing, SparkGrid supports Snowflake, MySQL, MariaDB, PostgreSQL, and Microsoft SQL Server databases. An account in one of these databases is required to use the application.
Highlights
- Spreadsheet-like interface to simplify and streamline database usage regardless of the user's SQL familiarity
- Rename, comment on, move, or delete database tables through a convenient alternate view
- Read-only mode for table analysis operations where data integrity is critical
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 30 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
t2.micro Recommended | $0.20 |
t3.micro | $0.20 |
r7a.2xlarge | $0.30 |
t3.nano | $0.20 |
t3a.nano | $0.20 |
m5a.2xlarge | $0.30 |
t3a.medium | $0.20 |
t3.2xlarge | $0.30 |
m5a.large | $0.30 |
r7a.medium | $0.20 |
Dimensions summary
You pay by the hour based on the AWS EC2 instance type you run SparkGrid on. Each dimension maps to a specific instance size, so the hourly rate scales with the compute, memory, and other resources that instance provides. The options span several instance families: general-purpose (t2, t3, t3a, m5, m5a), compute-optimized (c5d, c7a), and memory-optimized (r7a). Within a family, prices rise as you move from smaller sizes (nano, micro, small) up to larger ones (medium, large, xlarge, 2xlarge). You choose one instance type to match your workload and pay only for hours used.
Top-of-mind questions for buyers
You pay per hour for each running AWS EC2 instance where SparkGrid is deployed. The rate covers the software on that one instance, regardless of how many people use it. Each instance you launch bills separately. Your chosen instance type sets the hourly rate.
Hourly software charges apply while the instance runs. Stopping the instance halts the SparkGrid hourly charge. Stopped instances may still incur AWS storage fees for attached volumes, but the software meters running hours only. To stop all software charges, terminate the instance.
SparkGrid gives you a spreadsheet-style interface for working with cloud data warehouse tables. You add, delete, and edit rows and columns, then commit changes with one click. It previews changes as SQL statements and includes error handling and role-based table access. The hourly rate covers this software.
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Vendor refund policy
We do not currently offer refunds. To stop incurring hourly use fees, stop all instances running the service. No cancellation process is needed.
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Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
- Fixed an issue when changing between showing groups and rows when main columns are shown in descending order
- Standard machine updates
Also includes the changes from v1.5.0:
- Added MariaDB support
- Added support for a manual port number and database name when logging into non-Snowflake database systems
- Grid: Added a user option to group cells case-sensitively or case-insensitively
- Known issue: case sensitivity in MariaDB is only recognized if the rows-per-page option is set to 5000 (regardless of table size)
- Grid: Visually moved edited cell group values from the center to the top of the group to make finding values easier when editing large groups
- Grid: Prevented columns used in active filter or sort layers from being renamed or deleted
- Grid: Removed "rename column", "delete column", and "add column before" context menu options from the Group/ID Details and ID columns
- Column editor: Added a check against the default PRECISION value if one is not manually specified when changing a column to DEC
- Extended SQL Server's query timeout from 15 to 20 seconds
- Made minor wording changes and tooltip additions for clarity
- Tweaked blur/glass effects a bit
- Minor security improvements
- Several fixes, including:
- Updated to remove major dependency vulnerabilities, most notably upgrading snowflake-sdk to its current 2.x iteration
- Made some error handling improvements
- Fixed major issues when sorting ID columns in descending order
- Fixed renaming columns after editing their cells' contents
- Fixed deleting rows with edited ID values
- Fixed an issue with adding multiple new rows via the context menu
- Standard machine updates
Additional details
Usage instructions
Before following the steps below, make sure your EC2 instance is up and running.
- Access Your Instance:
- Enter "https://<ip_address>" or "http://<ip_address>" into your web browser, where "<ip_address>" is your instance's public IP address.
- To find the public IP address, go to your EC2 Management Console, select your instance, and look for the address listed there.
- If you choose "https://<ip_address>", you may receive a security warning. This is because the instance generates and signs its own HTTPS certificates upon startup, which allows a secure connection but cannot readily prove its identity. To proceed, select the "Advanced" or "Show Details" option, then select the option to continue, which may be worded as or like "Proceed to <ip_address> (unsafe)" or "Accept the risk and continue."
- Log In:
- Log in using your credentials from your Snowflake, MySQL, PostgreSQL, or SQL Server database of choice.
- For help logging in or using SparkGrid, check the documentation: https://sparksoftlabs.com/documents/products/SparkGrid-Documentation.pdf
- Enhance Security (optional but recommended):
- The instance's security group can limit SparkGrid access to specific IP addresses as needed.
- Running the SparkGrid instance within your organization's network security boundary can similarly restrict both inbound and outbound traffic.
Resources
Vendor resources
Support
Vendor support
You can reach us by email at sparkgridsupport@sparksoftcorp.com . Your message will reach our product's project director, marketing manager, and lead developer.
AWS infrastructure support
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