DBMS > LeanXcale vs. NSDb vs. Postgres-XL vs. TempoIQ

System Properties Comparison LeanXcale vs. NSDb vs. Postgres-XL vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.leanxcale.com

nsdb.io

www.postgres-xl.org

tempoiq.com (offline)

Technical documentation

nsdb.io/Architecture

www.postgres-xl.org/documentation

Developer

LeanXcale

TempoIQ

Initial release

2015

2017

2014

since 2012, originally named StormDB

2012

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Mozilla public license

commercial

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

Java, Scala

Server operating systems

Linux
macOS

Data scheme

yes

schema-free

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

yes

through Apache Derby

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

gRPC
HTTP REST
WebSocket

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

HTTP API

Supported programming languages

C
Java
Scala

Java
Scala

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

fine grained access rights according to SQL-standard

simple authentication-based access control

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