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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

A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Gravity Data Yes 
Amazon Web Services (AWS) Yes 
Amundsen Yes 
Apache Kafka Yes 
Apache Superset Yes 
DataHub Yes 
Hue Yes 
Manticore Search Yes 
Oracle Big Data Preparation No 
Oracle Cloud Infrastructure Data Catalog No 
Oracle Cloud Infrastructure Object Storage No 
Oracle Machine Learning No 
Oracle Partner Relationship Management No 
Oracle Subscription Management No 
Oracle Textura Pre-Qualification No 
Oracle Unity Customer Data Platform No 
Preset Yes 
RazorSQL Yes 
StrongDM Yes 
WisdomAI Yes 

Integrations

Gravity Data Yes 
Amazon Web Services (AWS) No 
Amundsen No 
Apache Kafka No 
Apache Superset No 
DataHub No 
Hue No 
Manticore Search No 
Oracle Big Data Preparation Yes 
Oracle Cloud Infrastructure Data Catalog Yes 
Oracle Cloud Infrastructure Object Storage Yes 
Oracle Machine Learning Yes 
Oracle Partner Relationship Management Yes 
Oracle Subscription Management Yes 
Oracle Textura Pre-Qualification Yes 
Oracle Unity Customer Data Platform Yes 
Preset No 
RazorSQL No 
StrongDM No 
WisdomAI No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
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 No 
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 Yes 
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

Kinetica

Founded

2009

Country

United States

Website

www.kinetica.com

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

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 

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting Yes 
Visualization Dashboards Yes 

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