DBMS > Datomic vs. EJDB vs. Graphite vs. Warp 10

System Properties Comparison Datomic vs. EJDB vs. Graphite vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

www.datomic.com

github.com/Softmotions/ejdb

github.com/graphite-project/graphite-web

www.warp10.io

Technical documentation

docs.datomic.com

github.com/Softmotions/ejdb/blob/master/README.md

graphite.readthedocs.io

www.warp10.io/content/02_Getting_started

Developer

Cognitect

Softmotions

Chris Davis

SenX

Initial release

2012

2006

2015

Current release

1.0.7180, July 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Python

Java

Server operating systems

All OS with a Java VM

server-less

Linux
Unix

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Numeric data only

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

APIs and other access methods

RESTful HTTP API

in-process shared library

HTTP API
Sockets

HTTP API
Jupyter
WebSocket

Supported programming languages

Clojure
Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

WarpScript

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

DB-Engines blog posts

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

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