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ease
features
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support

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Description

Apache Doris serves as a cutting-edge data warehouse tailored for real-time analytics, enabling exceptionally rapid analysis of data at scale. It features both push-based micro-batch and pull-based streaming data ingestion that occurs within a second, alongside a storage engine capable of real-time upserts, appends, and pre-aggregation. With its columnar storage architecture, MPP design, cost-based query optimization, and vectorized execution engine, it is optimized for handling high-concurrency and high-throughput queries efficiently. Moreover, it allows for federated querying across various data lakes, including Hive, Iceberg, and Hudi, as well as relational databases such as MySQL and PostgreSQL. Doris supports complex data types like Array, Map, and JSON, and includes a Variant data type that facilitates automatic inference for JSON structures, along with advanced text search capabilities through NGram bloomfilters and inverted indexes. Its distributed architecture ensures linear scalability and incorporates workload isolation and tiered storage to enhance resource management. Additionally, it accommodates both shared-nothing clusters and the separation of storage from compute resources, providing flexibility in deployment and management.

Description

The market experiences limited competition as a result of significant entry barriers, specialized expertise, substantial capital requirements, and extended time-to-market. Moreover, current platforms offer similar pricing and performance, which diminishes the motivation for users to transition. Transitioning from one SQL dialect to another can take months of intensive work. There is a demand for format-independent computing that can seamlessly work with all major open standards. Data leaders in enterprises are currently facing an extraordinary surge in the need for data intelligence. They are taken aback to discover that a mere 10% of their most demanding, compute-heavy tasks account for 80% of the costs, engineering resources, and stakeholder grievances. Regrettably, these workloads are also essential and cannot be neglected. e6data enhances the return on investment for a company's current data platforms and infrastructure. Notably, e6data’s format-agnostic computing stands out for its remarkable efficiency and performance across various leading data lakehouse table formats, thereby providing a significant advantage in optimizing enterprise operations. This innovative solution positions organizations to better manage their data-driven demands while maximizing their existing resources.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Hive
Apache Hudi
Amazon S3
Amazon Web Services (AWS)
Apache Avro
Apache Flink
Apache Parquet
Apache Spark
Baidu Palo
Delta
Google Cloud Platform
Iceberg
Microsoft Azure
MySQL
PostgreSQL
SelectDB
TapData
VeloDB

Integrations

Apache Hive
Apache Hudi
Amazon S3
Amazon Web Services (AWS)
Apache Avro
Apache Flink
Apache Parquet
Apache Spark
Baidu Palo
Delta
Google Cloud Platform
Iceberg
Microsoft Azure
MySQL
PostgreSQL
SelectDB
TapData
VeloDB

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

doris.apache.org

Vendor Details

Company Name

e6data

Founded

2020

Country

United States

Website

www.e6data.com

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Alternatives

Alternatives

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