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

GridDB vs VoltDB

OverviewComparisonAlternatives

Overview

VoltDB
VoltDB
Stacks18
Followers72
Votes18
GridDB
GridDB
Stacks3
Followers18
Votes0
GitHub Stars0
Forks0

VoltDB vs GridDB: What are the differences?

Developers describe VoltDB as "In-memory relational DBMS capable of supporting millions of database operations per second". 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. On the other hand, GridDB is detailed as "Open source time series database for IoT and Big Data". It is a highly scalable, in-memory NoSQL time series database optimized for IoT and Big Data. It has a KVS (Key-Value Store)-type data model that is suitable for sensor data stored in a timeseries. It is a database that can be easily scaled-out according to the number of sensors.

VoltDB and GridDB can be primarily classified as "In-Memory Databases" tools.

Some of the features offered by VoltDB are:

  • In-Memory Performance with On-Disk Durability
  • Transparent Scalability with Data Consistency
  • NewSQL – All the benefits of SQL with Unlimited Scalability

On the other hand, GridDB provides the following key features:

  • IoT Data Model
  • Distributed
  • Horizontal Scalability

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Detailed Comparison

VoltDB
VoltDB
GridDB
GridDB

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.

It is a highly scalable, in-memory NoSQL time series database optimized for IoT and Big Data. It has a KVS (Key-Value Store)-type data model that is suitable for sensor data stored in a timeseries. It is a database that can be easily scaled-out according to the number of sensors.

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
IoT Data Model; Distributed; Horizontal Scalability;In-memory;Hybrid Cluster Management;Fast Ingest;Composite Indexes;Petabyte-Scale DB size;Time series functions;Geometry data support
Statistics
GitHub Stars
-
GitHub Stars
0
GitHub Forks
-
GitHub Forks
0
Stacks
18
Stacks
3
Followers
72
Followers
18
Votes
18
Votes
0
Pros & Cons
Pros
  • 5
    SQL + Java
  • 4
    A brainchild of Michael Stonebraker
  • 4
    In-memory database
  • 3
    Very Fast
  • 2
    NewSQL
No community feedback yet
Integrations
No integrations available
Python
Python
Ubuntu
Ubuntu
Node.js
Node.js
CentOS
CentOS
Fluentd
Fluentd
openSUSE
openSUSE

What are some alternatives to VoltDB, GridDB?

Redis

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.

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.

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