DBMS > Amazon Redshift vs. GBase vs. HugeGraph vs. InfluxDB vs. Sqrrl

System Properties Comparison Amazon Redshift vs. GBase vs. HugeGraph vs. InfluxDB vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

A fast-speed and highly-scalable Graph DBMS

DBMS for storing time series, events and metrics

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Graph DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

with GEO package

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

aws.amazon.com/redshift

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

www.influxdata.com/products/influxdb-overview

sqrrl.com

Technical documentation

docs.aws.amazon.com/redshift

hugegraph.apache.org/docs

docs.influxdata.com/influxdb

Developer

Amazon (based on PostgreSQL)

General Data Technology Co., Ltd.

Baidu

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2004

2018

2013

2012

Current release

GBase 8a, GBase 8s, GBase 8c

0.9

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

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

Server operating systems

hosted

Linux

Linux
macOS
Unix

Linux
OS X

through Homebrew

Linux

Data scheme

yes

schema-free

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

restricted

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Standard with numerous extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
JSON over UDP

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

Groovy
Java
Python

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

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

Sharding

in enterprise version only

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

in enterprise version only

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

edges in graph

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

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

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Users, roles and permissions

simple rights management via user accounts

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

An Introductory Guide to Grafana Alerts
16 May 2024

What to Expect When You’re Expecting InfluxDB: A Guide
14 May 2024

Introduction to Apache Iceberg
9 May 2024

Converting Timestamp to Date in Java
7 May 2024

A Detailed Guide to C# TimeSpan
2 May 2024

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.