DBMS > KeyDB vs. NSDb vs. Postgres-XL vs. SwayDB vs. Transbase

System Properties Comparison KeyDB vs. NSDb vs. Postgres-XL vs. SwayDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Secondary database models

Document store
Spatial DBMS

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

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

github.com/Snapchat/KeyDB
keydb.dev

nsdb.io

www.postgres-xl.org

swaydb.simer.au

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

Technical documentation

docs.keydb.dev

nsdb.io/Architecture

www.postgres-xl.org/documentation

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

Developer

EQ Alpha Technology Ltd.

Simer Plaha

Transaction Software GmbH

Initial release

2019

2017

2014

since 2012, originally named StormDB

2018

1987

Current release

10 R1, October 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD-3

Open Source

Apache Version 2.0

Open Source

Mozilla public license

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

C++

Java, Scala

Scala

C and C++

Server operating systems

Linux

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

by using the Redis Search module

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Java
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Kotlin
Scala

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

Server-side scripts

Stored procedures

Lua

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

MVCC

Atomic execution of operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

fine grained access rights according to SQL-standard

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More resources

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