Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • RaimaDB Reviews & Ratings
    12 Ratings
    Company Website
  • QuantaStor Reviews & Ratings
    6 Ratings
    Company Website
  • PeerGFS Reviews & Ratings
    27 Ratings
    Company Website
  • Couchbase Reviews & Ratings
    415 Ratings
    Company Website
  • Dragonfly Reviews & Ratings
    16 Ratings
    Company Website
  • Declarative Webhooks Reviews & Ratings
    3 Ratings
    Company Website
  • Google Cloud Platform Reviews & Ratings
    60,586 Ratings
    Company Website
  • DbVisualizer Reviews & Ratings
    561 Ratings
    Company Website
  • Azore CFD Reviews & Ratings
    24 Ratings
    Company Website
  • ManageEngine ADManager Plus Reviews & Ratings
    632 Ratings
    Company Website

What is Voldemort?

Voldemort is not designed to operate as a relational database; it does not seek to maintain arbitrary relationships or comply with ACID principles. It also lacks the functionality of an object database that aims for a seamless mapping of object referencing. Moreover, it does not provide a new layer of abstraction like document orientation. Instead, it functions as a large, distributed, durable, and fault-tolerant hash table. For those employing an Object-Relational (O/R) mapper such as ActiveRecord or Hibernate, this setup can enhance horizontal scalability and availability significantly, though it comes with a notable loss of convenience. When dealing with large-scale applications that require internet-level scalability, systems often consist of multiple services or APIs that are functionally segmented, managing storage across diverse data centers, each with its own horizontally partitioned storage solutions. In such environments, executing arbitrary joins within the database can become unfeasible since not all data resides in a single database instance, which complicates data management further. Consequently, developers must shift their approaches to effectively cope with these limitations, necessitating a careful reevaluation of their data handling practices. This adjustment is crucial to ensure that the system remains efficient and responsive to the diverse needs of the applications it supports.

What is Apache Druid?

Apache Druid stands out as a robust open-source distributed data storage system that harmonizes elements from data warehousing, timeseries databases, and search technologies to facilitate superior performance in real-time analytics across diverse applications. The system's ingenious design incorporates critical attributes from these three domains, which is prominently reflected in its ingestion processes, storage methodologies, query execution, and overall architectural framework. By isolating and compressing individual columns, Druid adeptly retrieves only the data necessary for specific queries, which significantly enhances the speed of scanning, sorting, and grouping tasks. Moreover, the implementation of inverted indexes for string data considerably boosts the efficiency of search and filter operations. With readily available connectors for platforms such as Apache Kafka, HDFS, and AWS S3, Druid integrates effortlessly into existing data management workflows. Its intelligent partitioning approach markedly improves the speed of time-based queries when juxtaposed with traditional databases, yielding exceptional performance outcomes. Users benefit from the flexibility to easily scale their systems by adding or removing servers, as Druid autonomously manages the process of data rebalancing. In addition, its fault-tolerant architecture guarantees that the system can proficiently handle server failures, thus preserving operational stability. This resilience and adaptability make Druid a highly appealing option for organizations in search of dependable and efficient analytics solutions, ultimately driving better decision-making and insights.

Media

Media

Integrations Supported

Acryl Data
Amazon Web Services (AWS)
Amundsen
Apache Kafka
Apache Superset
Azure Marketplace
CelerData Cloud
Cloudera Data Warehouse
Emgage
Gravity Data
Hue
Imply
Manticore Search
Metabase
OpenMetadata
Preset
RazorSQL
Stackable

Integrations Supported

Acryl Data
Amazon Web Services (AWS)
Amundsen
Apache Kafka
Apache Superset
Azure Marketplace
CelerData Cloud
Cloudera Data Warehouse
Emgage
Gravity Data
Hue
Imply
Manticore Search
Metabase
OpenMetadata
Preset
RazorSQL
Stackable

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Voldemort

Company Website

www.project-voldemort.com/voldemort/

Company Facts

Organization Name

Druid

Date Founded

2013

Company Website

druid.apache.org/technology

Categories and Features

Data Replication

Asynchronous Data Replication
Automated Data Retention
Continuous Replication
Cross-Platform Replication
Dashboard
Instant Failover
Orchestration
Remote Database Replication
Reporting / Analytics
Simulation / Testing
Synchronous Data Replication

Categories and Features

Big Data

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

Data Warehouse

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

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

Popular Alternatives

RaimaDB Reviews & Ratings

RaimaDB

Raima

Popular Alternatives

FairCom DB Reviews & Ratings

FairCom DB

FairCom Corporation
Apache Cassandra Reviews & Ratings

Apache Cassandra

Apache Software Foundation
Apache Drill Reviews & Ratings

Apache Drill

The Apache Software Foundation
QuantaStor Reviews & Ratings

QuantaStor

OSNexus
CelerData Cloud Reviews & Ratings

CelerData Cloud

CelerData