DBMS > Amazon DocumentDB vs. Geode vs. GigaSpaces vs. RocksDB

System Properties Comparison Amazon DocumentDB vs. Geode vs. GigaSpaces vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Secondary database models

Graph DBMS
Search engine

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Trend Chart

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/documentdb

geode.apache.org

www.gigaspaces.com

rocksdb.org

Technical documentation

aws.amazon.com/documentdb/resources

geode.apache.org/docs

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Gigaspaces Technologies

Facebook, Inc.

Initial release

2019

2002

2000

2013

Current release

1.1, February 2017

15.5, September 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net

C++

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Solaris
Windows

Linux

Data scheme

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

SQL-99 for query and DML statements

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java Client API
Memcached protocol
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

yes, on a single node

ACID

yes

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

Access rights per client and object definable

Role-based access control

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