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features
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support

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Description

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

Description

Modern distributed messaging platforms like Kafka and Pulsar have established a robust Pub/Sub framework suitable for the demands of contemporary data-rich applications. Pravega takes this widely accepted programming model a step further by offering a cloud-native streaming infrastructure that broadens its applicability across various use cases. With features that ensure streams are durable, consistent, and elastic, Pravega also offers native support for long-term data retention. It addresses architectural challenges that earlier topic-centric systems such as Kafka and Pulsar have struggled with, including the automatic scaling of partitions and maintaining optimal performance despite a high volume of partitions. Additionally, Pravega expands the types of applications it can support by adeptly managing both small-scale events typical in IoT and larger data sets relevant to video processing and analytics. Beyond merely providing stream abstractions, Pravega facilitates the replication of application states and the storage of key-value pairs, making it a versatile choice for developers. This flexibility empowers users to create more complex and resilient data architectures tailored to their specific needs.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Kafka Yes 
Acryl Data Yes 
Apache Airflow Yes 
Apache Superset Yes 
Azure Marketplace Yes 
CelerData Cloud Yes 
Cloudera Data Warehouse Yes 
DataHub Yes 
EmailSuccess No 
Emgage Yes 
Hue Yes 
Imply Yes 
Metabase Yes 
OpenMetadata Yes 
Pulsar No 
RazorSQL Yes 
Stackable Yes 
StrongDM Yes 

Integrations

Apache Kafka Yes 
Acryl Data No 
Apache Airflow No 
Apache Superset No 
Azure Marketplace No 
CelerData Cloud No 
Cloudera Data Warehouse No 
DataHub No 
EmailSuccess Yes 
Emgage No 
Hue No 
Imply No 
Metabase No 
OpenMetadata No 
Pulsar Yes 
RazorSQL No 
Stackable No 
StrongDM No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Druid

Founded

2013

Website

druid.apache.org/technology

Vendor Details

Company Name

Pravega

Founded

2017

Country

United States

Website

pravega.io

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Relational Database

ACID Compliance No 
Data Failure Recovery No 
Multi-Platform No 
Referential Integrity No 
SQL DDL Support No 
SQL DML Support No 
System Catalog No 
Unicode Support No 

Product Features

Cloud Storage

Access Control No 
Archiving & Retention No 
Backup No 
Data Migration No 
Data Synchronization No 
Encryption No 
File Sharing No 
Version Control No 

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