DBMS > Apache Phoenix vs. EventStoreDB vs. KairosDB vs. Lovefield vs. Oracle NoSQL

System Properties Comparison Apache Phoenix vs. EventStoreDB vs. KairosDB vs. Lovefield vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Key-value store
Relational DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

phoenix.apache.org

www.eventstore.com

github.com/kairosdb/kairosdb

google.github.io/lovefield

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

phoenix.apache.org

developers.eventstore.com

kairosdb.github.io

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

Event Store Limited

Google

Oracle

Initial release

2014

2012

2013

2014

2011

Current release

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

21.2, February 2021

1.2.2, November 2018

2.1.12, February 2017

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Java

Server operating systems

Linux
Unix
Windows

Linux
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Solaris SPARC/x86

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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 query language

via JavaScript builder pattern

SQL-like DML and DDL statements

APIs and other access methods

JDBC

Graphite protocol
HTTP REST
Telnet API

RESTful HTTP API

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

JavaScript

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

off heap cache

User concepts

Access control

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

simple password-based access control

Access rights for users and roles

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More resources

DB-Engines blog posts

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