DBMS > Apache Phoenix vs. HugeGraph vs. Manticore Search

System Properties Comparison Apache Phoenix vs. HugeGraph vs. Manticore Search

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

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

Primary database model

Relational DBMS

Graph DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	2.02
Rank	#130	Overall
	#63	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.23
Rank	#317	Overall
	#21	Search engines

Website

phoenix.apache.org

github.com/hugegraph
hugegraph.apache.org

manticoresearch.com

Technical documentation

phoenix.apache.org

hugegraph.apache.org/docs

manual.manticoresearch.com

Developer

Apache Software Foundation

Baidu

Manticore Software

Initial release

2014

2018

2017

Current release

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

0.9

6.0, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2

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

Linux
Unix
Windows

Linux
macOS
Unix

FreeBSD
Linux
macOS
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Fixed schema

Typing

predefined data types such as float or date

yes

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

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

also supports composite index and range index

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

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

Supported programming languages

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

Groovy
Java
Python

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

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

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.

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

Users, roles and permissions

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

全面升级！Apache HugeGraph 1.2.0版本发布_apach hugegraph
27 February 2024, CSDN

HugeGraph 部署和Hubble1.0.0的数据导入Bug修复_hugegraph-hubble导入数据时选择属性显示不全
18 October 2023, CSDN

provided by Google News

Integrating Manticore Search with Apache Superset
8 August 2023, hackernoon.com

Comparing Meilisearch and Manticore Search Using Key Benchmarks
2 May 2023, hackernoon.com

Clickhouse vs Elasticsearch vs Manticore Search Query Times With a 1.7B NYC Taxi Rides Benchmark
1 June 2022, hackernoon.com

8 Google Alternatives: How to Search Crypto, the Dark Web, More
1 February 2023, Gizmodo

TF-IDF in a nutshell. Understanding TF-IDF evolution in 5… | by Sergey Nikolaev
13 April 2020, Towards Data Science

provided by Google News

Share this page