DBMS > EJDB vs. Graphite vs. TimesTen vs. YTsaurus

System Properties Comparison EJDB vs. Graphite vs. TimesTen vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

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

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store

Time Series DBMS

Relational DBMS

Document store
Key-value store

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

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.15
Rank	#323	Overall
	#44	Document stores
	#47	Key-value stores

Website

github.com/Softmotions/ejdb

github.com/graphite-project/graphite-web

www.oracle.com/database/technologies/related/timesten.html

ytsaurus.tech

Technical documentation

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

graphite.readthedocs.io

docs.oracle.com/en/database/other-databases/timesten/index.html

ytsaurus.tech/docs/en

Developer

Softmotions

Chris Davis

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Yandex

Initial release

2012

2006

1998

2023

Current release

Release 22.1

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

commercial

Open Source

Apache License, Version 2.0

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

Python

C++

Server operating systems

server-less

Linux
Unix

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Ubuntu

Data scheme

schema-free

yes

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

yes

YQL, an SQL-based language, is supported

APIs and other access methods

in-process shared library

HTTP API
Sockets

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

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

JavaScript (Node.js)
Python

C
C++
Java
Node.js
PL/SQL
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

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

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

Access Control Lists

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More resources

DB-Engines blog posts

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4 July 2016, Matthias Gelbmann

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1 June 2015, Paul Andlinger

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