DBMS > Couchbase vs. GigaSpaces vs. Oracle NoSQL vs. Sqrrl vs. ToroDB

System Properties Comparison Couchbase vs. GigaSpaces vs. Oracle NoSQL vs. Sqrrl vs. ToroDB

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Adaptable, secure NoSQL built on Apache Accumulo

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Document store
Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
Search engine

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.couchbase.com

www.gigaspaces.com

www.oracle.com/database/nosql/technologies/nosql

sqrrl.com

github.com/torodb/server

Technical documentation

docs.couchbase.com

docs.gigaspaces.com/latest/landing.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Couchbase, Inc.

Gigaspaces Technologies

Oracle

Amazon

originally Sqrrl Data, Inc.

8Kdata

Initial release

2011

2000

2011

2012

2016

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

15.5, September 2020

23.3, December 2023

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; Commercial licenses available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

AGPL-V3

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

C, C++, Go and Erlang

Java, C++, .Net

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux
Solaris SPARC/x86

Linux

All OS with a Java 7 VM

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

string, integer, double, boolean, date, object_id

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++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-99 for query and DML statements

SQL-like DML and DDL statements

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

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

RESTful HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C++
Java
Python
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

selectable replication factor

making use of Hadoop

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Atomic updates per row, document, or graph entity

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

Ephemeral buckets

yes

off heap cache

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Role-based access control

Access rights for users and roles

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

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