DBMS > InfluxDB vs. OrigoDB vs. RocksDB vs. Warp 10 vs. XTDB

System Properties Comparison InfluxDB vs. OrigoDB vs. RocksDB vs. Warp 10 vs. XTDB

Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

A fully ACID in-memory object graph database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Key-value store

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

with GEO package

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

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.influxdata.com/products/influxdb-overview

origodb.com

rocksdb.org

www.warp10.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.influxdata.com/influxdb

origodb.com/docs

github.com/facebook/rocksdb/wiki

www.warp10.io/content/02_Getting_started

www.xtdb.com/docs

Developer

Robert Friberg et al

Facebook, Inc.

SenX

Juxt Ltd.

Initial release

2013

2009

under the name LiveDB

2013

2015

2019

Current release

2.7.6, April 2024

8.11.4, April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

Open Source

Apache License 2.0

Open Source

MIT 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

C++

Java

Clojure

Server operating systems

Linux
OS X

through Homebrew

Linux
Windows

Linux

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

User defined using .NET types and collections

yes

yes, extensible-data-notation format

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API
JSON over UDP

.NET Client API
HTTP API
LINQ

C++ API
Java API

HTTP API
Jupyter
WebSocket

HTTP REST
JDBC

Supported programming languages

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

.Net

C
C++
Go
Java
Perl
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

Source-replica replication

yes

selectable replication factor

based on HBase

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

User concepts

Access control

simple rights management via user accounts

Role based authorization

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
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Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
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Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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Key customers

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

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Licensing and pricing models

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

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

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

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

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