Is your Database holding you hostage?

Resolve long-standing issues cost-effectively while achieving blazing fast performance.

Unleash the full potential of your data without burning a hole in your bank account.

I would like to get database change notifications via Redis. Otherwise, there is complexity in dealing with multiple push clients handling different operations at the same time.

CTO
Renewable Energy

A small, insignificant query can cause major problems when there is high concurrency. There is nothing to diagnose or fix when the individual query returns in 10ms. This is where developers fail to cache and end up with problems.

CTO
AI Voice Assistant

Throughput is an issue in supply chain where lots of data comes in. SQL Server does not scale well horizontally to meet the demanding response requirements when clients drop a lot of files

CTO
Supply Chain

This is a serious problem in the transactional space. We use Redis everywhere. It's on the high transaction apps where we start to run into challenges.

CTO
Consulting

DynamoDB can scale to infinite or as deep as your pockets will go. You can throw as much data as you want at it. It will never even stutter. But it's very expensive. Caching can reduce variable Disk IO costs.

CTO
Startup

Programming paradigms have changed with technologies like React, Hotwire and Turbo which require a different way of retrieving data from the server. This means use faster techniques like Redis, because the old way does not work well anymore.

Solution Architect

The industry struggles with legacy applications where a lot of code change is needed to introduce caching. Sometimes it can take a week, sometimes a month. It would be great to have a proxy layer which can cache transparently.

CPO
Mortgage Company

SQL Server is fairly effective in taking a one time hit for a query and caching for subsequent calls. However, it does not work very well for transactional data.

Senior Data Architect
IT Services

We are getting more and more requests for real-time reports. But we are unable to do that with the current system. There is a lag of almost 1 hour. Even now people are struggling because it takes a lot of time to access data via reports.

Data Architect
Non-Profit

A cache is needed to store about a million words (few MB) per call which needs to be held on till the end of the user session. This is important when a user is interacting with an LLM Chatbot over multiple messages in a session.

AI Engineer

We have been in your shoes

Even the best developers write inconsistent code.

SQL developers often become bottlenecks until optimization is no longer feasible.

DBAs are stretched thin with no time for major backlog items.

Urgent features remain six months away, year after year. If only we had the time, resources, or anything to spare.

Database performance has a threshold

Speed of data retrieval from disk has a threshold for all databases. There’s a limit to how far one can optimize application data models and queries to improve database latency and performance. Beyond that, squeezing out more performance is not possible. Assigning more resources or upgrading to better hosts with higher performance has limitations, where the database engine becomes a bottleneck. We didn’t say any of this!

Key Findings

We still write backend code using decades old, familiar techniques. Meanwhile, data access techniques have not evolved beyond stored procedures and ORM tools.

RDBMS is a dead-end

The features that gave you ACID compliance have made them unsuitable for modern workloads.

NoSQL is not the solution

Even NoSQL databases are limited by their inherent disk-optimized design.

The Cloud is expensive

Companies that achieve product-market fit, fail when expenses exceed revenue.

Scaling is expensive

Public Cloud companies make billions on elastic scalability & serverless computing. Even IO cycles cost money.

Redis takes time & effort

From startups to large enterprises, it takes everyone a long time to learn how to use it effectively.

CRUD takes a lot of work

Manually writing code for basic database operations and integrating caching w/ TTL in a consistent manner to avoid spaghetti code is challenging.

A Weak Foundation

Because applications are handwritten using unreusable, custom code, they become obsolete over time. The only opportunity to make significant improvements are at the get-go because changing anything later can break everything. What if the foundation for every app was reusable, and could independently evolve over time?

50x

Cyclomatic complexity per function/ module

20%

Technical Debt Ratio (TDR) in large apps

20

Typical number of defects per KLOC

3

Seconds or more latency is the norm, but considered slow

Learn more about our solution

Our mission is to advance data-driven Software Development by fundamentally reimagining it, leveraging decades of industry experience to transcend current limitations and challenges.