DataScript vs Redis

Overview

Redis

Stacks61.9K

Followers46.5K

Votes3.9K

GitHub Stars42

Forks6

DataScript

Stacks3

Followers7

Votes0

GitHub Stars5.7K

Forks313

DataScript vs Redis: What are the differences?

Introduction: In the world of databases, DataScript and Redis are two popular choices for storing and retrieving data. Let's explore some key differences between these two technologies.

Data Model: DataScript is an in-memory database that stores data as immutable values in an embedded database engine. By contrast, Redis is an in-memory data structure store that persists on disk and can be used as a database, cache, or message broker. This fundamental difference in data models can impact the way data is stored, queried, and managed in each system.
Data Querying: DataScript uses Datalog, a declarative query language, to query data stored in the database. On the other hand, Redis provides a set of commands for data manipulation and retrieval, making it more suited for key-value store operations. This distinction highlights the versatility of Redis for various use cases compared to the query-centric approach of DataScript.
Scalability: Redis is known for its ability to scale horizontally by adding more nodes to a cluster, allowing for distributed data storage and high availability. In contrast, DataScript's scalability is limited to a single in-memory database instance, which may impact performance and fault tolerance in large-scale applications with high data throughput requirements.
Data Persistence: Redis supports data persistence by periodically writing data from memory to disk, providing durability and fault tolerance in case of node failures. DataScript, being primarily an in-memory database, lacks built-in persistence mechanisms and relies on application-level strategies for data durability, making it more suitable for transient data or caching scenarios.
Programming Language Support: DataScript is predominantly used with Clojure, a functional programming language, while Redis offers client libraries for various programming languages such as Python, Java, and Node.js. This difference in programming language support can influence the ease of integration and adoption of each database technology within different development ecosystems.
Indexing and Performance: Redis uses indexes to quickly locate and retrieve data based on keys, enabling fast read and write operations even with large datasets. DataScript, on the other hand, relies on in-memory data structures for indexing and may not provide the same level of performance optimization as Redis in scenarios requiring frequent data lookups or updates.

In Summary, DataScript and Redis differ in their data models, querying mechanisms, scalability, persistence strategies, programming language support, and indexing performance, influencing their suitability for different types of applications and use cases.

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CLI (Node.js)

Manual

Detailed Comparison

Redis	DataScript
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 immutable in-memory database and Datalog query engine in Clojure and ClojureScript. It is meant to run inside the browser. It is cheap to create, quick to query and ephemeral. You create a database on page load, put some data in it, track changes, do queries and forget about it when the user closes the page.
-	Database as a value; Triple store model; EAVT, AEVT and AVET indexes; Multi-valued attributes; Implicit joins; Query over DB or regular collections
Statistics
GitHub Stars 42	GitHub Stars 5.7K
GitHub Forks 6	GitHub Forks 313
Stacks 61.9K	Stacks 3
Followers 46.5K	Followers 7
Votes 3.9K	Votes 0
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	No community feedback yet
Integrations
No integrations available	JavaScript Clojure ClojureScript

What are some alternatives to Redis, DataScript?

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 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 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

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

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.

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

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

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 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 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.

Related Comparisons

DataScript vs Redis: What are the differences?

Introduction: In the world of databases, DataScript and Redis are two popular choices for storing and retrieving data. Let's explore some key differences between these two technologies.

Data Model: DataScript is an in-memory database that stores data as immutable values in an embedded database engine. By contrast, Redis is an in-memory data structure store that persists on disk and can be used as a database, cache, or message broker. This fundamental difference in data models can impact the way data is stored, queried, and managed in each system.
Data Querying: DataScript uses Datalog, a declarative query language, to query data stored in the database. On the other hand, Redis provides a set of commands for data manipulation and retrieval, making it more suited for key-value store operations. This distinction highlights the versatility of Redis for various use cases compared to the query-centric approach of DataScript.
Scalability: Redis is known for its ability to scale horizontally by adding more nodes to a cluster, allowing for distributed data storage and high availability. In contrast, DataScript's scalability is limited to a single in-memory database instance, which may impact performance and fault tolerance in large-scale applications with high data throughput requirements.
Data Persistence: Redis supports data persistence by periodically writing data from memory to disk, providing durability and fault tolerance in case of node failures. DataScript, being primarily an in-memory database, lacks built-in persistence mechanisms and relies on application-level strategies for data durability, making it more suitable for transient data or caching scenarios.
Programming Language Support: DataScript is predominantly used with Clojure, a functional programming language, while Redis offers client libraries for various programming languages such as Python, Java, and Node.js. This difference in programming language support can influence the ease of integration and adoption of each database technology within different development ecosystems.
Indexing and Performance: Redis uses indexes to quickly locate and retrieve data based on keys, enabling fast read and write operations even with large datasets. DataScript, on the other hand, relies on in-memory data structures for indexing and may not provide the same level of performance optimization as Redis in scenarios requiring frequent data lookups or updates.

DataScript vs Redis

Overview