DBMS > atoti vs. EJDB vs. Hawkular Metrics vs. Quasardb vs. TimesTen

System Properties Comparison atoti vs. EJDB vs. Hawkular Metrics vs. Quasardb vs. TimesTen

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.

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

atoti.io

github.com/Softmotions/ejdb

www.hawkular.org

quasar.ai

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

Technical documentation

docs.atoti.io

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

www.hawkular.org/hawkular-metrics/docs/user-guide

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

Developer

ActiveViam

Softmotions

Community supported by Red Hat

quasardb

Oracle, TimesTen Performance Software, HP

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

Initial release

2012

2014

2009

1998

Current release

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free versions available

Open Source

GPLv2

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

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

server-less

Linux
OS X
Windows

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

yes

APIs and other access methods

in-process shared library

HTTP REST

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Go
Java
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Python

PL/SQL

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

based on Cassandra

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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, multi-version concurrency control (MVCC)

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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