DBMS > Badger vs. Pinecone vs. TimesTen vs. Transbase

System Properties Comparison Badger vs. Pinecone vs. TimesTen vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

In-Memory RDBMS compatible to Oracle

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store

Vector DBMS

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	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/dgraph-io/badger

www.pinecone.io

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

www.transaction.de/en/products/transbase.html

Technical documentation

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

docs.pinecone.io/docs/overview

docs.oracle.com/database/timesten-18.1

www.transaction.de/en/products/transbase/features.html

Developer

DGraph Labs

Pinecone Systems, Inc

Oracle, TimesTen Performance Software, HP

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

Transaction Software GmbH

Initial release

2017

2019

1998

1987

Current release

11 Release 2 (11.2.2.8.0)

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

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

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

String, Number, Boolean

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

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Python

C
C++
Java
PL/SQL

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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