DBMS > NSDb vs. Postgres-XL vs. TigerGraph vs. Valentina Server

System Properties Comparison NSDb vs. Postgres-XL vs. TigerGraph vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Object-relational database and reports server

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

Technical documentation

nsdb.io/Architecture

www.postgres-xl.org/documentation

docs.tigergraph.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Paradigma Software

Initial release

2017

2014

since 2012, originally named StormDB

2017

1999

Current release

10 R1, October 2018

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Mozilla public license

commercial

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, Scala

C++

Server operating systems

Linux
macOS

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

SQL-like query language (GSQL)

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

ODBC

Supported programming languages

Java
Scala

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

C++
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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