DBMS > GigaSpaces vs. NSDb vs. RocksDB

System Properties Comparison GigaSpaces vs. NSDb vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Key-value store

Secondary database models

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Trend Chart

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

www.gigaspaces.com

nsdb.io

rocksdb.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

nsdb.io/Architecture

github.com/facebook/rocksdb/wiki

Developer

Gigaspaces Technologies

Facebook, Inc.

Initial release

2000

2017

2013

Current release

15.5, September 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

Java, Scala

C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux
macOS

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

APIs and other access methods

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

gRPC
HTTP REST
WebSocket

C++ API
Java API

Supported programming languages

.Net
C++
Java
Python
Scala

Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Role-based access control

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