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Row Zero is the best spreadsheet for big data. It enables operations, finance, marketing, and other business teams to securely analyze and work with big data sets in a familiar and flexible spreadsheet. Row Zero can open 1 billion row data sets, connect directly to data warehouses, and support multi-user collaboration to make working with hosted data easy for anyone with spreadsheet skills. Because Row Zero spreadsheets run in the cloud, they eliminate the security risk of CSV exports and locally stored Excel spreadsheets. Row Zero closes the last-mile analysis gap helping business teams take insights from dashboards and turn them into actionable results.
Row Zero Features:
Speed and Performance - Row Zero is a spreadsheet that leverages cloud computing strategies to enable users to import, open, and interact, cell-by-cell, with 1 billion row data sets, like they would in Excel and Google Sheets but on a larger scale.
Connectivity - Row Zero’s native connections to data warehouses provide efficiency gains for business teams who, instead of building one-off static analyses, like financial models and demand forecasts, can build them once using a connected table and schedule automated refresh. Row Zero also enables saving data from the spreadsheet to the data warehouse.
Collaboration - In order for data analysis to be valuable the work must be shared across teams, business units, and organizations. For this reason, Row Zero workbooks can be shared with viewer and editor permissions and support real-time collaboration for group work and facilitating efficient presentations.
Governance – Row Zero runs in the cloud, enables sharing permissions (viewer and editor), and enforces data permissions from the data warehouses, eliminating the security risk of downloaded CSVs and emailed .xlsx files.
Security - Row Zero is SOC2 Type II certified and HIPAA compliant. The SOC II report and a BAA are available upon request.
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Row Zero's answer:
Row Zero is the world's fastest spreadsheet, designed for big data sets. If a user already knows how to use a spreadsheet and needs to analyze or transform large data sets, Row Zero is the perfect tool. Data teams that serve large businesses can off-load ad-hoc and last mile analytics requests by enabling their business partners to work in Row Zero.
Row Zero's answer:
Row Zero's is a last mile analytics tool that enables business teams (marketing, operations, finance, etc...) to connect to cloud data warehouses and work with big data sets in a spreadsheet they already know how to use. BI tools are great for high level metric monitoring but the work initiated as a result of those dashboards needs to happen in a tool where business teams can see and interact with their data.
Row Zero's answer:
Business teams that need to work with big data sets but prefer a spreadsheet over writing SQL or rigid BI tools.
Row Zero's answer:
Row Zero was born out of our own frustrations doing data analysis on big data sets. Excel and Google Sheets don't easily connect to cloud data warehouses and have small row limits. We needed to open multi-million row data sets and analyze them quickly. Row Zero is the highly performant tool we wish we'd had.
Row Zero's answer:
Based on our record, Row Zero should be more popular than Supermemory. It has been mentiond 8 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.
This is usually a challenge that any developer has to take care of when building an AI agent. In fact, managing the context is one of the hardest problems when working with AI agents and there are many companies like SuperMemory, Mem0 which have invested both resources and time to solve this problem. - Source: dev.to / about 1 month ago
Memory. I use Supermemory for this. Before, Pipa loaded context files and knew to update them. A memory tool adds teammate-like recall: goals, preferences, latest business state, and small details that should carry across runs. Good memory tools also know how to supersede and delete memories, which matters once the agent has more autonomy. - Source: dev.to / 3 months ago
We wire everything up with Vision Agents as the voice agent framework, Stream for WebRTC audio and video, OpenAI Realtime for speech in and speech out, Anam so the agent shows up as a face on the video, and Supermemory so answers come from search over your uploaded documents instead of guesswork. The code stays small and most of the behavior lives in one registered function that asks the memory store for relevant... - Source: dev.to / 4 months ago
My friends and I are working on https://supermemory.ai, an AI second brain to help you remember content from saved webpages and notes. - Source: Hacker News / about 2 years ago
Try https://rowzero.com ? We have written a much faster spreadsheet engine and regularly work with 10M+ row datasets. - Source: Hacker News / 5 months ago
How large are you talking about? Have you tried https://rowzero.io? - Source: Hacker News / 11 months ago
You should check out Row Zero (https://rowzero.io). We launched on HN earlier this year. Our CSV handling is the best on the market. You can import multi GB csvs, we auto infer your format, and land your data in a full-featured spreadsheet that supports filter, sort, ctrl-F, sharing, graphs, the full Excel formula language, native Python, and export to Postgres, Snowflake, and Databricks. - Source: Hacker News / almost 2 years ago
I've been working on a better spreadsheet for a while now. https://rowzero.io is 1000x faster spreadsheet than Excel/Google Sheets. It looks and feels like those products but can open multi GB data sets, supports Python natively, and can also connect directly to Snowflake/Databricks/Redshift. - Source: Hacker News / about 2 years ago
We built our spreadsheet (https://rowzero.io) from the ground up to integrate natively with Python. Bolting it on like Microsoft did, or as an add in like xlwings, just feels second class. To make it first class, we had to solve three hard problems: 1. Sandboxing and dependencies. Python is extremely unsafe to share, so you need to sandbox execution. There's also the environment/package management problem (does... - Source: Hacker News / about 2 years ago
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