DBMS > Apache Phoenix vs. Google BigQuery vs. Manticore Search vs. Oracle Coherence

System Properties Comparison Apache Phoenix vs. Google BigQuery vs. Manticore Search vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Multi-storage database for search, including full-text search.

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Search engine

Key-value store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

phoenix.apache.org

cloud.google.com/bigquery

manticoresearch.com

www.oracle.com/java/coherence

Technical documentation

phoenix.apache.org

cloud.google.com/bigquery/docs

manual.manticoresearch.com

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

Developer

Apache Software Foundation

Google

Manticore Software

Oracle

Initial release

2014

2010

2017

2007

Current release

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

6.0, February 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

Linux
Unix
Windows

hosted

FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JCache
JPA
RESTful HTTP API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

yes, with selectable consistency level

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

yes

isolated transactions for atomic changes and binary logging for safe writes

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

optionally

In-memory capabilities

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

yes

User concepts

Access control

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

authentification to access the cache via certificates or http basic authentication

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