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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. Redis vs VoltDB

Redis vs VoltDB

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
VoltDB
VoltDB
Stacks18
Followers72
Votes18

Redis vs VoltDB: What are the differences?

Introduction

Redis and VoltDB are both popular in-memory databases used for different purposes. While Redis is a key-value store primarily used for caching and persistent storage, VoltDB is an in-memory relational database that focuses on high-speed transaction processing. Let's explore the key differences between Redis and VoltDB.

  1. Data Model: Redis stores data as key-value pairs, allowing various data types such as strings, lists, sets, hashes, and sorted sets. On the other hand, VoltDB supports a relational data model with tables, rows, and columns, enabling more complex data structures and relationships.

  2. ACID Compliance: Redis is not strictly ACID compliant as it sacrifices durability for performance, making it suitable for scenarios where data loss can be tolerated. In contrast, VoltDB fully adheres to the ACID (Atomicity, Consistency, Isolation, Durability) principles, ensuring data integrity at all times.

  3. Scaling Strategy: Redis can be scaled horizontally using clustering techniques, allowing data to be distributed across multiple nodes. In VoltDB, scaling is achieved through shared-nothing partitioning, where data is partitioned across different servers to ensure high availability and performance.

  4. Concurrency Control: Redis provides simple concurrency control mechanisms such as optimistic locking and transactions. VoltDB, on the other hand, employs a distributed concurrency control mechanism called serializable snapshot isolation (SSI), ensuring consistent and serializable execution of transactions.

  5. Use Cases: Redis is often used for caching, session management, real-time analytics, and pub/sub messaging due to its fast read and write performance. VoltDB, with its strong ACID compliance and high-speed transaction processing capabilities, is well-suited for applications that require high-volume data ingestion, real-time decision-making, and fraud detection.

  6. Durability and Persistence: Redis supports different levels of persistence, including snapshots and append-only logs. However, it primarily relies on an in-memory storage approach, which means that data can be lost in the event of a system crash. In contrast, VoltDB provides durable storage by replicating data across multiple servers, ensuring no data loss even in failure scenarios.

In summary, Redis and VoltDB differ in their data models, ACID compliance, scaling strategies, concurrency control mechanisms, use cases, and durability approaches. Redis offers a flexible key-value store for caching and persistent storage, while VoltDB focuses on high-speed transaction processing with a relational data model.

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Detailed Comparison

Redis
Redis
VoltDB
VoltDB

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

-
In-Memory Performance with On-Disk Durability;Transparent Scalability with Data Consistency;NewSQL – All the benefits of SQL with Unlimited Scalability;JSON Support for Agile Development;ACID Compliant Transactions;Export Data to OLAP Stores and Data Warehouses
Statistics
GitHub Stars
42
GitHub Stars
-
GitHub Forks
6
GitHub Forks
-
Stacks
61.9K
Stacks
18
Followers
46.5K
Followers
72
Votes
3.9K
Votes
18
Pros & Cons
Pros
  • 888
    Performance
  • 542
    Super fast
  • 514
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
Cons
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
Pros
  • 5
    SQL + Java
  • 4
    A brainchild of Michael Stonebraker
  • 4
    In-memory database
  • 3
    Very Fast
  • 2
    NewSQL

What are some alternatives to Redis, VoltDB?

Hazelcast

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

Tarantool

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Azure Redis Cache

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

KeyDB

KeyDB

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

LokiJS

LokiJS

LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.

BuntDB

BuntDB

BuntDB is a low-level, in-memory, key/value store in pure Go. It persists to disk, is ACID compliant, and uses locking for multiple readers and a single writer. It supports custom indexes and geospatial data. It's ideal for projects that need a dependable database and favor speed over data size.

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