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MemSQL

83
182
+ 1
32
VoltDB

17
69
+ 1
18
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MemSQL vs VoltDB: What are the differences?

1. Scalability: MemSQL boasts of horizontal as well as vertical scalability, making it suitable for varying workloads and data volumes. On the other hand, VoltDB primarily focuses on horizontal scalability, thereby excelling in scenarios requiring high transaction throughput with low-latency requirements.

2. Consistency Model: MemSQL follows a typical distributed database model with its use of synchronous replication, allowing for strong consistency guarantees. In contrast, VoltDB utilizes a partition-based architecture along with its single-threaded execution model to provide serializable isolation levels, ensuring strong consistency in distributed environments.

3. Query Optimization: MemSQL incorporates a cost-based query optimizer that enhances query performance by generating optimal execution plans. Meanwhile, VoltDB leverages stored procedures to mitigate network overhead and latency, offering improved performance for transactional workloads.

4. Data Storage: MemSQL can support a hybrid architecture with a combination of in-memory and disk-based storage for efficient data processing. On the contrary, VoltDB is an in-memory database system, ensuring high-speed data access and processing capabilities without the need for disk storage, ideal for real-time data processing requirements.

5. Architecture: MemSQL follows a traditional shared-nothing architecture, enabling efficient distribution of data and processing across nodes in a cluster. In contrast, VoltDB employs an in-memory, lock-free, distributed architecture that ensures linear scalability and fault tolerance without sacrificing performance, making it suitable for high-demand transactional applications.

6. Use Cases: MemSQL is well-suited for analytical workloads, complex queries, and real-time dashboarding due to its hybrid storage capabilities and robust query optimization features. Conversely, VoltDB is ideal for use cases that require high-speed, high-throughput transaction processing, such as financial services, gaming, telecommunications, and real-time analytics applications.

In Summary, MemSQL and VoltDB differ in scalability options, consistency models, query optimization techniques, data storage approaches, architectural designs, and targeted use cases, catering to distinct data processing needs and workload requirements.

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Pros of MemSQL
Pros of VoltDB
  • 8
    Distributed
  • 4
    Realtime
  • 3
    Sql
  • 3
    Concurrent
  • 3
    JSON
  • 3
    Columnstore
  • 2
    Scalable
  • 2
    Ultra fast
  • 1
    Availability Group
  • 1
    Mixed workload
  • 1
    Pipeline
  • 1
    Unlimited Storage Database
  • 5
    SQL + Java
  • 4
    In-memory database
  • 4
    A brainchild of Michael Stonebraker
  • 3
    Very Fast
  • 2
    NewSQL

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What is 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.

What is 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.

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Jobs that mention MemSQL and VoltDB as a desired skillset
LaunchDarkly
Oakland, California, United States
What companies use MemSQL?
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What are some alternatives to MemSQL and VoltDB?
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.
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.
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.
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.
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
See all alternatives