DBMS > Badger vs. Oracle NoSQL vs. SpaceTime vs. TimescaleDB vs. ToroDB

System Properties Comparison Badger vs. Oracle NoSQL vs. SpaceTime vs. TimescaleDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store

Document store
Key-value store
Relational DBMS

Spatial DBMS

Time Series DBMS

Document store

Secondary database models

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

github.com/dgraph-io/badger

www.oracle.com/database/nosql/technologies/nosql

www.mireo.com/spacetime

www.timescale.com

github.com/torodb/server

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

docs.timescale.com

Developer

DGraph Labs

Oracle

Mireo

Timescale

8Kdata

Initial release

2017

2011

2020

2017

2016

Current release

24.1, May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

Apache 2.0

Open Source

AGPL-V3

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++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux

Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

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

yes

string, integer, double, boolean, date, object_id

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

A subset of ANSI SQL is implemented

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

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

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
C++
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Fixed-grid hypercubes

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Real-time block device replication (DRBD)

Source-replica replication with hot standby and reads on replicas

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

none

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

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