DBMS > Amazon Neptune vs. LMDB vs. Netezza vs. Tkrzw

System Properties Comparison Amazon Neptune vs. LMDB vs. Netezza vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A high performant, light-weight, embedded key-value database library

Data warehouse and analytics appliance part of IBM PureSystems

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

aws.amazon.com/neptune

www.symas.com/symas-embedded-database-lmdb

www.ibm.com/products/netezza

dbmx.net/tkrzw

Technical documentation

aws.amazon.com/neptune/developer-resources

www.lmdb.tech/doc

Developer

Amazon

Symas

IBM

Mikio Hirabayashi

Initial release

2017

2011

2000

2020

Current release

0.9.32, January 2024

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

hosted

Linux
Unix
Windows

Linux

included in appliance

Linux
macOS

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC
OLE DB

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C
C++
Fortran
Java
Lua
Perl
Python
R

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept

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