DBMS > Apache Phoenix vs. LokiJS vs. Oracle Coherence vs. Tarantool

System Properties Comparison Apache Phoenix vs. LokiJS vs. Oracle Coherence vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

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

In-memory JavaScript DBMS

Oracles in-memory data grid solution

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Document store

Key-value store

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	2.02
Rank	#130	Overall
	#63	Relational DBMS

Score	0.48
Rank	#262	Overall
	#42	Document stores

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	1.67
Rank	#150	Overall
	#25	Document stores
	#25	Key-value stores
	#69	Relational DBMS

Website

phoenix.apache.org

github.com/techfort/LokiJS

www.oracle.com/java/coherence

www.tarantool.io

Technical documentation

phoenix.apache.org

techfort.github.io/LokiJS

docs.oracle.com/en/middleware/standalone/coherence

www.tarantool.io/en/doc

Developer

Apache Software Foundation

Oracle

Initial release

2014

2007

2008

Current release

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

14.1, August 2023

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

C and C++

Server operating systems

Linux
Unix
Windows

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

All OS with a Java VM

BSD
Linux
macOS

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

via views

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC

JavaScript API

JCache
JPA
RESTful HTTP API

Open binary protocol

Supported programming languages

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

JavaScript

.Net
C++
Java

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

Lua, C and SQL stored procedures

Triggers

yes

Live Events

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, with selectable consistency level

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

none

Eventual Consistency
Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

configurable

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

optionally

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

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

authentification to access the cache via certificates or http basic authentication

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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1 December 2014, Matthias Gelbmann

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Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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