DBMS > Amazon DocumentDB vs. GridGain vs. Heroic vs. Warp 10

System Properties Comparison Amazon DocumentDB vs. GridGain vs. Heroic vs. Warp 10

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

GridGain is an in-memory computing platform, built on Apache Ignite

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

aws.amazon.com/documentdb

www.gridgain.com

github.com/spotify/heroic

www.warp10.io

Technical documentation

aws.amazon.com/documentdb/resources

www.gridgain.com/docs/index.html

spotify.github.io/heroic

www.warp10.io/content/02_Getting_started

Developer

GridGain Systems, Inc.

Spotify

SenX

Initial release

2019

2007

2014

2015

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

commercial, open source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net, Python, REST, SQL

Java

Server operating systems

hosted

Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

WarpScript

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes (replicated cache)

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

Role-based access control
Security Hooks for custom implementations

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

Unlock the power of Amazon DocumentDB text search with real-world use cases
5 March 2024, AWS Blog

Update your Amazon DocumentDB TLS certificates: Expiring in 2024
28 March 2024, AWS Blog

provided by Google News

GridGain Advances Its Unified Real-Time Data Platform to Help Enterprises Accelerate AI-Driven Data Processing
10 July 2024, insideBIGDATA

GridGain Sponsoring Strategic AI and Kafka Conferences This Month
4 September 2024, Datanami

GridGain in-memory data and generative AI
10 May 2024, Blocks & Files

Data Management News for the Week of July 12; Updates from Cloudera, HerculesAI, Oracle & More
12 July 2024, Solutions Review

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, Datanami

provided by Google News

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of Developers
28 June 2017, PR Newswire

provided by Google News

Share this page