DBMS > GBase vs. Hive vs. InfluxDB vs. Lovefield vs. Snowflake

System Properties Comparison GBase vs. Hive vs. InfluxDB vs. Lovefield vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.gbase.cn

hive.apache.org

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

www.snowflake.com

Technical documentation

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

docs.influxdata.com/influxdb

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

docs.snowflake.net/manuals/index.html

Developer

General Data Technology Co., Ltd.

Apache Software Foundation

initially developed by Facebook

Google

Snowflake Computing Inc.

Initial release

2004

2012

2013

2014

Current release

GBase 8a, GBase 8s, GBase 8c

3.1.3, April 2022

2.7.6, April 2024

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

Java

JavaScript

Server operating systems

Linux

All OS with a Java VM

Linux
OS X

through Homebrew

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

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Thrift

HTTP API
JSON over UDP

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

in enterprise version only

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Depending on used storage engine

yes

using MemoryDB

User concepts

Access control

yes

Access rights for users, groups and roles

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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