DBMS > Alibaba Cloud Table Store vs. EsgynDB vs. InfluxDB vs. STSdb vs. VoltDB

System Properties Comparison Alibaba Cloud Table Store vs. EsgynDB vs. InfluxDB vs. STSdb vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

DBMS for storing time series, events and metrics

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.esgyn.cn

www.influxdata.com/products/influxdb-overview

github.com/STSSoft/STSdb4

www.voltdb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.influxdata.com/influxdb

docs.voltdb.com

Developer

Alibaba

Esgyn

STS Soft SC

VoltDB Inc.

Initial release

2016

2015

2013

2011

2010

Current release

2.7.6, April 2024

4.0.8, September 2015

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

GPLv2, commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

hosted

Linux

Linux
OS X

through Homebrew

Windows

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC

HTTP API
JSON over UDP

.NET Client API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC/ADO.Net

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

C#
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

in enterprise version only

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication between multi datacenters

selectable replication factor

in enterprise version only

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic single-row operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

simple rights management via user accounts

Users and roles with access to stored procedures

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

Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB
6 June 2024

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
5 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 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.

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

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Getting Started with Alibaba Cloud
30 May 2024, O'Reilly Media

Apache Software Foundation Announces New Top-Level Project Apache Paimon
16 April 2024, Datanami

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

25 Best Cloud Service Providers (Public and Private) in 2024
4 June 2023, CybersecurityNews

provided by Google News

Amazon Timestream for InfluxDB is now generally available
15 March 2024, AWS Blog

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World
14 March 2024, businesswire.com

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

provided by Google News

Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News

Share this page