DBMS > atoti vs. Derby vs. InfluxDB vs. LevelDB vs. Postgres-XL

System Properties Comparison atoti vs. Derby vs. InfluxDB vs. LevelDB vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

DBMS for storing time series, events and metrics

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

atoti.io

db.apache.org/derby

www.influxdata.com/products/influxdb-overview

github.com/google/leveldb

www.postgres-xl.org

Technical documentation

docs.atoti.io

db.apache.org/derby/manuals/index.html

docs.influxdata.com/influxdb

github.com/google/leveldb/blob/main/doc/index.md

www.postgres-xl.org/documentation

Developer

ActiveViam

Apache Software Foundation

Google

Initial release

1997

2013

2011

2014

since 2012, originally named StormDB

Current release

10.17.1.0, November 2023

2.7.6, April 2024

1.23, February 2021

10 R1, October 2018

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache version 2

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

Open Source

Mozilla public license

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

All OS with a Java VM

Linux
OS X

through Homebrew

Illumos
Linux
OS X
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC

HTTP API
JSON over UDP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Python

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

in enterprise version only

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

in enterprise version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

simple rights management via user accounts

fine grained access rights according to SQL-standard

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

A Detailed Guide to C# TimeSpan
2 May 2024

The Final Frontier: Using InfluxDB on the International Space Station
30 April 2024

Getting the Current Time in C#: A Guide
26 April 2024

Sync Data from InfluxDB v2 to v3 With the Quix Template
8 April 2024

Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana
5 April 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

Best use of cloud: ActiveViam
28 November 2023, Risk.net

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

JDBC tutorial: Easy installation and setup with Apache Derby
20 December 2019, TheServerSide.com

Top Database Tools for Java Developers in 2023
17 November 2023, TechRepublic

Installing Apache Hive 3.1.2 on Windows 10 | by Hadi Fadlallah
3 May 2020, Towards Data Science

The Arrival of Java 20
21 March 2023, Oracle

No, Citrix did not kill CloudStack
15 September 2014, InfoWorld

provided by Google News

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 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, Business Wire

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

Time-series database startup InfluxData debuts self-managed version of InfluxDB
6 September 2023, SiliconANGLE News

provided by Google News

LevelDB in Ruby — SitePoint
22 October 2014, SitePoint

Microsoft Teams stores auth tokens as cleartext in Windows, Linux, Macs
14 September 2022, BleepingComputer

Pliops unveils XDP-Rocks for RocksDB – Blocks and Files
19 October 2022, Blocks and Files

XanMod, Liquorix Kernels Offer Some Advantages On AMD Ryzen 5 Notebook
26 July 2021, Phoronix

Rust-Based Info Stealers Abuse GitHub Codespaces
19 May 2023, Trend Micro

provided by Google News

Share this page