DBMS > atoti vs. Graphite vs. RocksDB

System Properties Comparison atoti vs. Graphite vs. RocksDB

Please select another system to include it in the comparison.

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Primary database model

Object oriented DBMS

Time Series DBMS

Key-value store

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

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

Website

atoti.io

github.com/graphite-project/graphite-web

rocksdb.org

Technical documentation

docs.atoti.io

graphite.readthedocs.io

github.com/facebook/rocksdb/wiki

Developer

ActiveViam

Chris Davis

Facebook, Inc.

Initial release

2006

2013

Current release

8.11.4, April 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

BSD

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

Python

C++

Server operating systems

Linux
Unix

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

Numeric data only

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

APIs and other access methods

HTTP API
Sockets

C++ API
Java API

Supported programming languages

JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

locking

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

User concepts

Access control

More information provided by the system vendor

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.