DBMS > Apache Pinot vs. Galaxybase vs. Google BigQuery vs. Hive vs. HugeGraph

System Properties Comparison Apache Pinot vs. Galaxybase vs. Google BigQuery vs. Hive vs. HugeGraph

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Scalable, ACID-compliant native distributed parallel graph platform

Large scale data warehouse service with append-only tables

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A fast-speed and highly-scalable Graph DBMS

Primary database model

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

pinot.apache.org

galaxybase.com

cloud.google.com/bigquery

hive.apache.org

github.com/hugegraph
hugegraph.apache.org

Technical documentation

docs.pinot.apache.org

cloud.google.com/bigquery/docs

cwiki.apache.org/confluence/display/Hive/Home

hugegraph.apache.org/docs

Developer

Apache Software Foundation and contributors

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Apache Software Foundation

initially developed by Facebook

Baidu

Initial release

2015

2017

2010

2012

2018

Current release

1.0.0, September 2023

Nov 20, November 2021

3.1.3, April 2022

0.9

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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 and Java

Java

Server operating systems

All OS with a Java JDK11 or higher

Linux

hosted

All OS with a Java VM

Linux
macOS
Unix

Data scheme

yes

Strong typed schema

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Go
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

Groovy
Java
Python

Server-side scripts

Stored procedures

user defined procedures and functions

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

edges in graph

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

Role-based access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

Users, roles and permissions

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