DBMS > Apache Drill vs. Geode vs. GigaSpaces vs. PouchDB vs. RocksDB

System Properties Comparison Apache Drill vs. Geode vs. GigaSpaces vs. PouchDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Document store
Relational DBMS

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Document store

Key-value store

Secondary database models

Graph DBMS
Search engine

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

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

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

Score	2.28
Rank	#115	Overall
	#21	Document stores

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

Website

Technical documentation

drill.apache.org/docs

geode.apache.org/docs

docs.gigaspaces.com/latest/landing.html

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

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

Gigaspaces Technologies

Apache Software Foundation

Facebook, Inc.

Initial release

2012

2002

2000

2012

2013

Current release

1.20.3, January 2023

1.1, February 2017

15.5, September 2020

7.1.1, June 2019

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

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

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Java, C++, .Net

JavaScript

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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

via views

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language (OQL)

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

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

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Supported programming languages

C++

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

.Net
C++
Java
Python
Scala

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

View functions in JavaScript

Triggers

yes

Cache Event Listeners

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes, on a single node

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Access rights per client and object definable

Role-based access control

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