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Databricks & Arbisoft

Unify your data estate on the Databricks data intelligence platform with Arbisoft. From ingestion to production, we help you operationalize machine learning, streamline data engineering, and deliver governed, real-time insights — all within a single, scalable platform built for enterprise-grade performance.

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1000s of High-Profile Companies Across all Industries Trust Databricks

Over 10,000 companies across the world, including Comcast, Shell, Grammarly, and more than 50% of the Fortune 500, leverage Databricks to unify their data, analytics, and AI. (Wonder why?)

Know why Databricks is the perfect choice for all your data needs

Databricks combines the strengths of a data warehouse, which stores structured data in a centralized repository, and a data lake, which holds large amounts of raw, unprocessed data, thus offering you the best of both worlds.

  • Unified analytics platform

    It brings everything from data engineering to analytics and AI onto a single, unified platform, so your work stays connected and your team remains in sync.

  • End-to-end ML support

    From data preparation to deployment, Databricks allows you to effectively manage the entire machine learning (ML) lifecycle within a single, unified platform.

  • Interoperability

    Databricks easily integrates with your preferred cloud (Azure, Google Cloud, AWS) and makes it easy for you to safely share data across platforms.

  • Better collaboration

    Databricks provides a collaborative workspace where multiple users can work together using shared notebooks and their preferred programming languages.

  • Data diversity

    Databricks is suitable for all data types and sizes. This enables your organization to handle complex data landscapes with greater effectiveness.

  • Rock-solid security

    With Unity Catalog, Databricks centralizes access control, auditing, and data lineage to keep your data and workloads safe and compliant.

How Databricks Compares with Snowflake

Given below is a breakdown of how Databricks stacks up across key features when compared to Snowflake, one of its direct competitors.

Feature / Functionality
Databricks
Snowflake
Service model
Databricks
PaaS
Snowflake
SaaS
Who's it for
Databricks
Data engineers, data scientists, analysts, and those with data ownership
Snowflake
Data analysts
Data types supported
Databricks
All data types (raw, audio, video, logs, text, etc.)
Snowflake
Primarily semi-structured and structured data
Key services
Databricks
Data engineering, data science, data analytics, machine learning
Snowflake
Database management and data warehouse
Provisioning of different types of nodes
Databricks
Yes
Snowflake
No
AI/ML features
Databricks
Extensive native support for ML and AI workloads
Snowflake
Limited, relies on external integration for advanced ML/AI
Query interface
Databricks
Supports SQL, Spark DataFrame, Koalas
Snowflake
SQL-based queries
Query performance
Databricks
Excels in handling big data and complex computations
Snowflake
Optimized for smaller, business intelligence workloads
Scaling
Databricks
Scales automatically based on workload demands
Snowflake
Scales automatically up to 128 nodes
Data sharing
Databricks
Open Delta Sharing
Snowflake
Proprietary data sharing via a marketplace
Vendor lock in
Databricks
No
Snowflake
Yes

Databricks Services by Arbisoft

As a Databricks consulting partner, Arbisoft offers a full range of Databricks services to help you migrate, implement, optimize, and build data and AI solutions. Whether you’re getting started with Databricks, exploring advanced analytics, or looking to enhance your existing platform, our experts are ready to support you every step of the way.

Our Databricks consultants provide expert advice and strategic guidance, covering architecture, strategy, and optimization to help you get the most out of your data.

We specialize in end-to-end Databricks implementation. Our solutions align with your business goals and help you harness the true power of Databricks.

We optimize your data pipelines, fine-tune clusters, improve job performance, and monitor resources to maximize efficiency and lower operational costs.

We help you migrate your on-prem and legacy data systems to the Databricks lakehouse platform while ensuring minimal downtime and maximized efficiency.

We provide expertise in Databricks data engineering to assist you in creating, deploying, and scaling data pipelines optimized for analytics and AI workloads.

Our Databricks experts help you derive actionable insights from large datasets through advanced modeling, predictive analytics, clustering, time series analysis, and more.

We work with you to comprehensively assess your existing Databricks environment for security, reliability, scalability, operational excellence, and cost effectiveness.

You can count on us to build and deploy AI and ML solutions that fully tap into Databricks' AI/ML capabilities, including tools like AutoML and MLFlow.

We'll help you create custom dashboards and reporting solutions using Databricks and configure AI/BI Genie to get you answers fast without relying on experts.

Our Databricks experts can help you develop custom GenAI applications by using open-source LLM DBRX for scalable, high-performance solutions tailored to your needs.

We're a Certified Databricks Consulting Partner

Arbisoft is proud to have a dedicated team of 25+ certified Databricks experts, including data engineering professionals & associates, data analyst associates, and GenAI experts, to guide and support you through the Databricks implementation journey.

Here's How Data Teams Are Leveraging Databricks Across Industries

Financial Services

A global financial data provider, facing post-merger infrastructure challenges, needed to unify diverse data sources and democratize access to insights. With Databricks, they were able to process 700 billion data points easily from a centralized platform, allowing them to do deeper ESG analysis, mitigate credit risk, and seamlessly share data with clients and partners.

700B+

data points processed from a centralized platform

65%

boost in cost efficiency after phasing out legacy systems

950+

active users on the platform, up from just 3 in 2018

Healthcare

A leading American healthcare company struggled to handle millions of daily claims and meet critical turnaround times using a legacy Oracle system. Migrating to Databricks allowed them to modernize their data infrastructure and workflows, allowing faster claims processing and millions saved annually.

1 M

claims processed daily

2x

increase in claims processing speed

$Millions

in potential revenue loss prevented

Media & Publishing

A global media company serving 100M+ monthly visitors needed to streamline their fragmented infrastructure to handle growing data volumes and deliver personalized content. By moving to Databricks, they simplified their data stack and now use AI to deliver smart, cross-channel recommendations that help grow subscriptions and keep audiences engaged.

2000

ML models running in production

2M

recommendations served daily

$6M

saved in IT costs

Our Databricks Implementation & Deployment Process

At Arbisoft, we follow a comprehensive 6-step process that ensures your Databricks adoption journey is smooth and optimized for performance and scalability.

  1. 01

    Assessment & planning

    We begin by analyzing your data sources, processing requirements, security considerations, and scalability needs to develop a comprehensive strategy that aligns with your business goals.

  2. 02

    Architecture Design & Data Modeling

    We design a future-ready Databricks architecture by choosing the right clusters, storage, and integrations. Our data modeling strategies organize raw data into well-structured, analytics-ready formats, powering faster insights, real-time reporting.

  3. 03

    Data integration & Migration

    In this phase, we connect your existing data sources and migrate workloads to Databricks. Our team ensures a smooth migration of your datasets, pipelines, and workflows with minimal disruption.

  4. 04

    Security & Compliance Setup

    To protect your sensitive data, our team implements robust security measures. We configure role-based access controls, apply encryption, and ensure all the compliance standards are in place.

  5. 05

    Deployment & Support

    In the final stage, our team implements the Databricks platform and conducts rigorous testing to ensure everything functions properly. Plus, we also remain available for ongoing optimization and troubleshooting needs in the future.

All the A's to Your Q's

  • Databricks is not just an ETL tool. While it does provide strong ETL capabilities, its core strength lies in being a unified data intelligence platform. It is designed to support the entire data lifecycle, from data engineering to analytics and AI workflows, all in one place.

  • Databricks allows you to store and process all types of data in its original format. This includes structured, semi-structured, and unstructured data in formats like CSVs, JSON files, images, videos, and even streaming data.

  • Databricks brings data engineering, data science, and business analytics together on one unified platform. From ingesting and preparing data to exploring, modeling, and visualizing it, you can do it all in one collaborative space, keeping everything connected and your team aligned.

  • Yes, Databricks is a strong platform for machine learning and AI. It supports many libraries, including popular ones like TensorFlow and Pytorch, and comes with MLflow for managing the entire machine learning lifecycle. Databricks also supports AutoML for faster deployment and enables scalable model training on large datasets.

  • Databricks offers Delta Sharing, an open protocol for secure, real-time data sharing. It allows you to collaborate with your partners and customers across different platforms, ensuring consistent data privacy controls and seamless data exchange without replication.

  • Databricks can run on various cloud platforms, including AWS, Azure, Google Cloud, and Alibaba Cloud. This flexibility allows businesses to choose the cloud provider that best suits their infrastructure and operational needs.

  • The Databricks implementation cost depends on several factors. These factors may include the Databricks features you require, the complexity and size of your data environment, the scope of integration, the level of customization needed, and whether you want services like user training and ongoing support. To get an accurate estimate of your project, get in touch with us today.

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