DBMS > GigaSpaces vs. KairosDB vs. NSDb vs. SwayDB vs. Transbase

System Properties Comparison GigaSpaces vs. KairosDB vs. NSDb vs. SwayDB vs. Transbase

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

Distributed Time Series DBMS based on Cassandra or H2

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

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Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.gigaspaces.com

github.com/kairosdb/kairosdb

nsdb.io

swaydb.simer.au

www.transaction.de/en/products/transbase.html

Technical documentation

docs.gigaspaces.com/latest/landing.html

kairosdb.github.io

nsdb.io/Architecture

www.transaction.de/en/products/transbase/features.html

Developer

Gigaspaces Technologies

Simer Plaha

Transaction Software GmbH

Initial release

2000

2013

2017

2018

1987

Current release

15.5, September 2020

1.2.2, November 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

commercial

free development license

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, C++, .Net

Java

Java, Scala

Scala

C and C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

yes

APIs and other access methods

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

Graphite protocol
HTTP REST
Telnet API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C++
Java
Python
Scala

Java
JavaScript

Node.js
PHP
Python

Java
Scala

Java
Kotlin
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

based on Cassandra

none

Source-replica replication

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

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

simple password-based access control

fine grained access rights according to SQL-standard

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