DBMS > BigObject vs. Ehcache vs. TimescaleDB

System Properties Comparison BigObject vs. Ehcache vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

bigobject.io

www.ehcache.org

www.timescale.com

Technical documentation

docs.bigobject.io

www.ehcache.org/documentation

docs.timescale.com

Developer

BigObject, Inc.

Terracotta Inc, owned by Software AG

Timescale

Initial release

2015

2009

2017

Current release

3.10.0, March 2022

2.13.0, November 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

full PostgreSQL SQL syntax

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JCache

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

fine grained access rights according to SQL-standard

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