DBMS > Hive vs. LeanXcale vs. Newts vs. Quasardb

System Properties Comparison Hive vs. LeanXcale vs. Newts vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

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

Score	81.61
Rank	#17	Overall
	#11	Relational DBMS

Score	0.18
Rank	#292	Overall
	#42	Key-value stores
	#136	Relational DBMS

Score	0.00
Rank	#354	Overall
	#33	Time Series DBMS

Score	0.11
Rank	#310	Overall
	#28	Time Series DBMS

Website

hive.apache.org

www.leanxcale.com

opennms.github.io/newts

quasardb.net

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

Developer

Apache Software Foundation

initially developed by Facebook

LeanXcale

OpenNMS Group

quasardb

Initial release

2012

2015

2014

2009

Current release

3.1.2, August 2019

3.13.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through Apache Derby

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST
Java API

HTTP API

Supported programming languages

C++
Java
PHP
Python

C
Java
Scala

Java

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

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

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights for users, groups and roles

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

Full ACID and full SQL operational database with analytical queries over operational...
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High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
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Competitive advantages

Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
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High performance in a cost-effective small package Real-time results for even large...
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Typical application scenarios

Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
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Tick database Predictive maintenance Pre-deal checks Large scale monitoring
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Key customers

banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
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Large EU investment banks US based hedge funds Orolia Tellmeplus
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Market metrics

15 beta testers
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Has been running in very demanding production environments since 2013 Rapid adoption...
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Licensing and pricing models

annual fee covering license and support based on number of physical cores
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Community edition limited to 2 nodes and 16 GiB of storage per node available for...
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