DBMS > atoti vs. Ehcache vs. Hive vs. Sadas Engine vs. SpaceTime

System Properties Comparison atoti vs. Ehcache vs. Hive vs. Sadas Engine vs. SpaceTime

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.

A widely adopted Java cache with tiered storage options

data warehouse software for querying and managing large distributed datasets, built on Hadoop

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Secondary database models

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

www.mireo.com/spacetime

Technical documentation

docs.atoti.io

www.ehcache.org/documentation

cwiki.apache.org/confluence/display/Hive/Home

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

ActiveViam

Terracotta Inc, owned by Software AG

Apache Software Foundation

initially developed by Facebook

SADAS s.r.l.

Mireo

Initial release

2009

2012

2006

2020

Current release

3.10.0, March 2022

3.1.3, April 2022

8.0

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2

commercial

free trial version available

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

All OS with a Java VM

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

yes

A subset of ANSI SQL is implemented

APIs and other access methods

JCache

JDBC
ODBC
Thrift

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

Supported programming languages

Java

C++
Java
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C#
C++
Python

Server-side scripts

Stored procedures

Python

yes

user defined functions and integration of map-reduce

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

by using Terracotta Server

Sharding

horizontal partitioning

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

selectable replication factor

none

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles

Access rights for users, groups and roles according to SQL-standard

yes

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

DZone Coding Java JBoss 5 to 7 in 11 steps
9 January 2014, dzone.com

provided by Google News

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

DataCentral: Uber's Observability and Chargeback Platform
1 February 2024, Uber

provided by Google News

Share this page