DBMS > Apache Phoenix vs. HEAVY.AI vs. Kinetica vs. NuoDB vs. SQLite

System Properties Comparison Apache Phoenix vs. HEAVY.AI vs. Kinetica vs. NuoDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Fully vectorized database across both GPUs and CPUs

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

phoenix.apache.org

github.com/heavyai/heavydb
www.heavy.ai

www.kinetica.com

www.3ds.com/nuodb-distributed-sql-database

www.sqlite.org

Technical documentation

www.sqlite.org/docs.html

Developer

Apache Software Foundation

HEAVY.AI, Inc.

Kinetica

Dassault Systèmes

originally NuoDB, Inc.

Dwayne Richard Hipp

Initial release

2014

2016

2012

2013

2000

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

5.10, January 2022

7.1, August 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

limited edition free

Open Source

Public Domain

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++ and CUDA

C, C++

C++

Server operating systems

Linux
Unix
Windows

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

server-less

Data scheme

yes

late-bound, schema-on-read capabilities

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

Java, SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Source-replica replication

yes

Managed transparently by NuoDB

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

Temporary table

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Standard SQL roles/ privileges, Administrative Users

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.