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A Unified Platform To Discover New Insights

  • Make The Right Data Available With Optimized Data Pipelining

    Data ingestion is vital for an enterprise data lake as it facilitates the constant intake of various data formats, ensuring real-time analysis and actionable insights, thereby optimizing decision-making processes.

  • Satisfy Your Key Stakeholders With A Securely Governed Data Platform

    Data governance is essential for a data lake to ensure data quality, compliance, and security, enabling effective management, usage, and trustworthiness of the vast and variety of data stored within the data lake.

  • Capture Transactions And Inform Just-In-Time Decisions With Real-Time Streaming

    Streaming transactions are vital for a data lake as they enable real-time data ingestion, processing, and analysis, ensuring timely insights and rapid response to changing conditions, enhancing operational efficiency, and enabling proactive decision-making.

SOLIXCloud Enterprise Data Lake - Third Generation Cloud Data Platform

SOLIXCloud Enterprise Data Lake is a response to a critical challenge in the digital landscape to help you turn your data into the asset it deserves to be and deliver new business-transforming insights. With data volumes projected to reach 175 zettabytes by 2025 - IT organizations are under immense pressure to manage growing volumes of enterprise data. At the same time, rising demand for real-time enterprise data to feed downstream systems requires new infrastructure solutions. SOLIXCloud Enterprise Data Lake enables you to safely govern, pipeline, process and warehouse enterprise data.

Built on the cloud-native Solix Common Data Platform (CDP), SOLIXCloud Enterprise Data Lake is a transactional, streaming data lake that supports ACID transactions and brings core data warehouse and database functionality directly to a data lake. Designed as a high-performance cloud database solution, the SOLIXCloud Enterprise Data Lake supports Open Table Formats for Apache Hudi, Apache Iceberg, and Delta.

SOLIXCloud Enterprise Data Lake Key Features


Fast Data Processing

Fast Data Processing

Reimagine slow, old-school batch data processing with a powerful new incremental approach to reading and writing data using real-time ingestion. Fast Data Processing runs alongside batch data processing and is ideal for incremental data ingestion into HDFS or to re-think and re-engineer ETL/Hive/Spark jobs which are slow running and taking up a lot of resources.

High-Performance Loading

High-Performance Loading

Even moderately big NoSQL database installations store billions of rows, making full bulk loads infeasible and a more efficient approach necessary to ingest such data volume. Replace costly and inefficient bulk loads with managed ingestion via Upserts and incremental streaming to keep your data up to date.

High-Performance Loading


Change Data Capture (CDC)

Change Data Capture (CDC)

Change data capture enables seamless, efficient database ingestion into your data lake. SOLIXCloud Enterprise Data Lake is designed to support fast Upserts and Deletes of data suitable for CDC and streaming use cases.

Cloud Database

Cloud Database

Features include Tables, Transactions, Change Data Capture, Upserts/Deletes, Advanced Indexes, Streaming Ingestion, Clustering/Compaction Optimizations, Transactional Writes, Snapshots, and Isolated reads for Concurrency control, all while keeping your data in open source file formats and ensuring your infrastructure is not tied to any one vendor.

Cloud Database


ACID Transactions

ACID Transactions

SOLIXCloud Enterprise Data Lake delivers transactional guarantees to your data lake with consistent, atomic writes and concurrency controls tailored for longer-running data lake transactions. Scale writes and reads independently to improve performance and optimize infrastructure.

Data Catalog

Data Catalog

Data scientists and data professionals require a detailed inventory of all data assets to help quickly find the most appropriate data for any analytical or business purpose. Features include role based access control, business glossary, data classification, metadata repository and data lineage.

Data Catalog


Data Preparation

Data Preparation

To create high quality data sets that are fit-for-use by AI/ML and advanced analytics, robust data engineering tools are required for data profiling, data cleansing, data enrichment, data transformation and data modeling. By removing erroneous records, tagging and labeling files, masking sensitive data, or combining data objects into enterprise business records, Solix Data Preparation improves machine learning and advanced analytics results.

Low-Code Incremental Pipelines & Continuous Data Delivery

Low-Code Incremental Pipelines & Continuous Data Delivery

A Continuous Data Delivery processing framework is ideal for low latency, minute-level analytics and change data capture workloads. Create declarative templates for incremental ingestion and transformation, and provision continuous data delivery pipelines for machine learning operations. Automate the operational burdens of scheduling, monitoring and moving enterprise data.

Low-Code Incremental Pipelines & Continuous Data Delivery


Machine Learning Operations (MLOps)

Machine Learning Operations (MLOps)

Support the entire machine learning lifecycle with MLOps from crafting and evaluation to data engineering and deployment. Integrate LLMs into your applications, deploy LLMs out of the box, or fine-tune SOLIX GPT on your data. Use SOLIXCloud Enterprise Data Lake and Solix ML to train advanced AI models in any cloud environment with data privacy, security, and compliance control.

Apache Spark

Apache Spark

Apache Spark’s parallel in-memory data processing is the world’s most widely used engine for scalable computations against structured and unstructured data. Thousands of companies, including 80% of the Fortune 500, use Apache Spark™ today.

Apache Spark


Federated Data Governance

Federated Data Governance

Federated Data Governance provides a centralized control framework for when several groups have authority over the data. Through check-in and check-out, delegated authorities, virtual policy enforcement and audit management, Federated Data Governance reduces risk, enables strong compliance controls and improves security and data privacy over decentralized data operations.

Real-time Streaming

Real-time Streaming

A real-time streaming data lake gathers, organizes, and analyzes continuously flowing data without fixed structures. It accommodates structured, semi-structured, and unstructured data, enabling real-time insights and decision-making.

Real-time Streaming

Get Started with SOLIXCloud Enterprise Data Lake

Unlock the power of your data with SolixCloud Enterprise Data Lake. Request a personalized demo today and discover how our Cloud Data Management platform can revolutionize the way you store, manage, and analyze data. Our team of experts will guide you through the features and capabilities of SolixCloud Enterprise Data Lake, demonstrating how it can streamline your data operations, improve efficiency, and drive business insights. Don't miss out on this opportunity to harness the full potential of your data.

Why SOLIXCloud?

SOLIXCloud Enterprise Archiving delivers a fully managed low-cost, scalable, elastic, secure, and compliant data management solution for all enterprise data.

  • Single Platform

    Single Platform

    Unified archive for structured, unstructured and semi-structured data.

  • Reduce Risk

    Reduce Risk

    Policy driven archiving and data retention

  • 24/7 Global Support

    24/7 Support

    Solix offers world-class support from experts 24/7 to meet your data management needs.

  • On-demand Scale

    On-demand Scale

    Elastic offering to scale storage and support with your project

  • Fully Managed

    Fully Managed

    Software as-a-service offering

  • Secure & Compliant

    Secure & Compliant

    Comprehensive Data Governance

  • Low Cost & Pay-as-you-go

    Low Cost

    Pay-as-you-go monthly subscription so you only purchase what you need.

  • End-User Friendly

    End-User Friendly

    End-user data access with flexibility for format options.

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