StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. Redis vs SAP HANA

Redis vs SAP HANA

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
SAP HANA
SAP HANA
Stacks169
Followers148
Votes27

Redis vs SAP HANA: What are the differences?

Redis vs SAP HANA

Redis and SAP HANA are both popular in-memory data stores used in different scenarios. While they have some similarities, they also have key differences that set them apart from each other. In this article, we will explore six key differences between Redis and SAP HANA.

  1. Data Model: Redis is a key-value store that allows you to store simple data structures like strings, lists, sets, and hashes. On the other hand, SAP HANA is a fully-fledged relational database management system (RDBMS) that supports SQL queries and complex data models like tables, views, and stored procedures. This makes SAP HANA suitable for handling structured data and performing sophisticated analytics.

  2. Scalability: Redis offers built-in support for distributed caching and data replication, allowing you to scale horizontally by adding more Redis nodes. However, SAP HANA provides scaling options through vertical and horizontal scaling, allowing you to increase the computational power and storage capacity of the system as your needs grow. SAP HANA's scalability options make it more suitable for handling large volumes of data and complex workloads.

  3. Query Language: Redis does not have a built-in query language like SQL. Instead, it provides a set of commands for data manipulation and retrieval. In contrast, SAP HANA uses SQL as its query language, allowing you to perform complex queries and aggregations on the data stored in the system. SQL's expressive power makes SAP HANA a more flexible choice for querying and analyzing data.

  4. Data Persistence: Redis offers both in-memory and disk-based data persistence options. You can configure Redis to periodically save snapshots of the in-memory data to disk or append changes to a log file for durability. On the other hand, SAP HANA stores data persistently on disk by default, ensuring data durability even in the event of a system failure. This makes SAP HANA more suitable for storing critical and persistent data.

  5. Use Cases: Redis is commonly used for caching, session management, and real-time analytics due to its low latency and high throughput capabilities. Its simplicity and fast data access make it a good choice for applications that require rapid data retrieval. However, SAP HANA is preferred for scenarios that involve complex data processing, predictive analytics, and real-time data integration. Its advanced features enable businesses to derive actionable insights from their data and make data-driven decisions.

  6. Cost: Redis is an open-source solution that can be used free of charge. However, if you require additional features or enterprise-level support, you may need to purchase a commercial license or subscribe to a managed Redis service. On the other hand, SAP HANA is a proprietary software that requires licensing fees. The cost of SAP HANA can vary depending on the edition and deployment options chosen. It is essential to consider the overall cost of ownership when deciding between Redis and SAP HANA.

In summary, Redis and SAP HANA differ in terms of their data model, scalability options, query language, data persistence, use cases, and cost. Understanding these differences is crucial for selecting the right data store based on the specific requirements and constraints of your application or system.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

Redis
Redis
SAP HANA
SAP HANA

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.

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.

-
processes transactions and analytics at the same time; built-in advanced analytics and multi-model data processing engines
Statistics
GitHub Stars
42
GitHub Stars
-
GitHub Forks
6
GitHub Forks
-
Stacks
61.9K
Stacks
169
Followers
46.5K
Followers
148
Votes
3.9K
Votes
27
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
  • 5
    In-memory
  • 4
    Performance
  • 4
    Distributed
  • 2
    Realtime
Integrations
No integrations available
Python
Python
Power BI
Power BI
Tableau
Tableau

What are some alternatives to Redis, SAP HANA?

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

VoltDB

VoltDB

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.

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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase