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features
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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

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amundsen Yes 
Astro by Astronomer Yes 
Azure Marketplace Yes 
DataHub Yes 
Deep.BI Yes 
Hue Yes 
Metabase Yes 
Stackable Yes 
Alteryx No 
Apache Bigtop No 
Apache Superset Yes 
Baidu Palo No 
Coginiti No 
Prophecy No 
Querona No 
Quorso No 
Rational BI No 
StrongDM Yes 
VeloDB No 
Yottamine No 

Integrations

Amundsen Yes 
Astro by Astronomer Yes 
Azure Marketplace Yes 
DataHub Yes 
Deep.BI Yes 
Hue Yes 
Metabase Yes 
Stackable Yes 
Alteryx Yes 
Apache Bigtop Yes 
Apache Superset No 
Baidu Palo Yes 
Coginiti Yes 
Prophecy Yes 
Querona Yes 
Quorso Yes 
Rational BI Yes 
StrongDM No 
VeloDB Yes 
Yottamine Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

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 No 

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Druid

Founded

2013

Website

druid.apache.org/technology

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org

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

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 Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting No 
Visualization Dashboards No 

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