MemSQL vs Oracle

Overview

MemSQL

Stacks86

Followers184

Votes44

Oracle

Stacks2.6K

Followers1.8K

Votes113

MemSQL vs Oracle: What are the differences?

## MemSQL vs Oracle

MemSQL is a distributed, in-memory, SQL database designed for high performance analytics and real-time business intelligence. On the other hand, Oracle is a relational database management system that offers a wide range of database services and features. 

1. **Architecture**: MemSQL is designed as a distributed system that can scale out horizontally, allowing it to handle large volumes of data and provide high availability. In contrast, Oracle follows a traditional architecture with a master-slave setup, which may limit its scalability for massive data processing.
  
2. **In-Memory Processing**: MemSQL primarily operates in-memory, enabling faster data processing and analytics. Oracle, although capable of in-memory processing, may not offer the same level of performance optimization for real-time analytics as MemSQL does.

3. **SQL Compatibility**: Both MemSQL and Oracle support SQL queries, but MemSQL often provides better compatibility with standard SQL queries and syntax. Oracle, on the other hand, may have its own proprietary SQL extensions and functionalities that differ from traditional SQL standards.

4. **Data Storage**: MemSQL's design focuses on keeping data in memory for faster access, while also providing disk-based storage options. Oracle traditionally relies on disk-based storage, with the option for in-memory storage that may not be as optimized as MemSQL for real-time processing.

5. **Integration with Big Data Technologies**: MemSQL is built to integrate seamlessly with various big data technologies such as Apache Kafka and Spark, offering easier integration with modern data processing frameworks. Oracle, while also providing integration options, may not offer the same level of compatibility and ease of integration with the latest big data technologies.

6. **License and Cost**: MemSQL may be more cost-effective for certain use cases, as it offers different licensing models, including open source options. Oracle, as a commercial database system, may have higher licensing costs for enterprise deployments.

In Summary, MemSQL and Oracle differ in terms of architecture, in-memory processing, SQL compatibility, data storage approaches, integration with big data technologies, and licensing costs.

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Advice on MemSQL, Oracle

Daniel

Data Engineer at Dimensigon

Jul 18, 2020

Decided

We have chosen Tibero over Oracle because we want to offer a PL/SQL-as-a-Service that the users can deploy in any Cloud without concerns from our website at some standard cost. With Oracle Database, developers would have to worry about what they implement and the related costs of each feature but the licensing model from Tibero is just 1 price and we have all features included, so we don't have to worry and developers using our SQLaaS neither. PostgreSQL would be open source. We have chosen Tibero over Oracle because we want to offer a PL/SQL that you can deploy in any Cloud without concerns. PostgreSQL would be the open source option but we need to offer an SQLaaS with encryption and more enterprise features in the background and best value option we have found, it was Tibero Database for PL/SQL-based applications.

496k views496k

Comments

Abigail

Dec 6, 2019

Decided

In the field of bioinformatics, we regularly work with hierarchical and unstructured document data. Unstructured text data from PDFs, image data from radiographs, phylogenetic trees and cladograms, network graphs, streaming ECG data... none of it fits into a traditional SQL database particularly well. As such, we prefer to use document oriented databases.

MongoDB is probably the oldest component in our stack besides Javascript, having been in it for over 5 years. At the time, we were looking for a technology that could simply cache our data visualization state (stored in JSON) in a database as-is without any destructive normalization. MongoDB was the perfect tool; and has been exceeding expectations ever since.

Trivia fact: some of the earliest electronic medical records (EMRs) used a document oriented database called MUMPS as early as the 1960s, prior to the invention of SQL. MUMPS is still in use today in systems like Epic and VistA, and stores upwards of 40% of all medical records at hospitals. So, we saw MongoDB as something as a 21st century version of the MUMPS database.

540k views540k

Comments

Abigail

Dec 10, 2019

Decided

We wanted a JSON datastore that could save the state of our bioinformatics visualizations without destructive normalization. As a leading NoSQL data storage technology, MongoDB has been a perfect fit for our needs. Plus it's open source, and has an enterprise SLA scale-out path, with support of hosted solutions like Atlas. Mongo has been an absolute champ. So much so that SQL and Oracle have begun shipping JSON column types as a new feature for their databases. And when Fast Healthcare Interoperability Resources (FHIR) announced support for JSON, we basically had our FHIR datalake technology.

558k views558k

Comments

Detailed Comparison

MemSQL	Oracle
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.	Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
ANSI SQL Support;Fully-distributed Joins;Compiled Queries; ACID Compliance;In-Memory Tables;On-Disk Tables; Massively Parallel Execution;Lock Free Data Structures;JSON Support; High Availability; Online Backup and Restore;Online Replication	-
Statistics
Stacks 86	Stacks 2.6K
Followers 184	Followers 1.8K
Votes 44	Votes 113
Pros & Cons
Pros 9 Distributed 5 Realtime 4 Columnstore 4 Sql 4 JSON	Pros 44 Reliable 33 Enterprise 15 High Availability 5 Hard to maintain 5 Expensive Cons 14 Expensive
Integrations
Google Compute Engine MySQL QlikView	No integrations available

What are some alternatives to MemSQL, Oracle?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

Redis

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.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Related Comparisons

MemSQL vs Oracle: What are the differences?

## MemSQL vs Oracle

MemSQL is a distributed, in-memory, SQL database designed for high performance analytics and real-time business intelligence. On the other hand, Oracle is a relational database management system that offers a wide range of database services and features. 

1. **Architecture**: MemSQL is designed as a distributed system that can scale out horizontally, allowing it to handle large volumes of data and provide high availability. In contrast, Oracle follows a traditional architecture with a master-slave setup, which may limit its scalability for massive data processing.
  
2. **In-Memory Processing**: MemSQL primarily operates in-memory, enabling faster data processing and analytics. Oracle, although capable of in-memory processing, may not offer the same level of performance optimization for real-time analytics as MemSQL does.

3. **SQL Compatibility**: Both MemSQL and Oracle support SQL queries, but MemSQL often provides better compatibility with standard SQL queries and syntax. Oracle, on the other hand, may have its own proprietary SQL extensions and functionalities that differ from traditional SQL standards.

4. **Data Storage**: MemSQL's design focuses on keeping data in memory for faster access, while also providing disk-based storage options. Oracle traditionally relies on disk-based storage, with the option for in-memory storage that may not be as optimized as MemSQL for real-time processing.

5. **Integration with Big Data Technologies**: MemSQL is built to integrate seamlessly with various big data technologies such as Apache Kafka and Spark, offering easier integration with modern data processing frameworks. Oracle, while also providing integration options, may not offer the same level of compatibility and ease of integration with the latest big data technologies.

6. **License and Cost**: MemSQL may be more cost-effective for certain use cases, as it offers different licensing models, including open source options. Oracle, as a commercial database system, may have higher licensing costs for enterprise deployments.

In Summary, MemSQL and Oracle differ in terms of architecture, in-memory processing, SQL compatibility, data storage approaches, integration with big data technologies, and licensing costs.

MemSQL vs Oracle

Overview