DBMS > BoltDB vs. HBase vs. Pinecone vs. RocksDB vs. Ultipa

System Properties Comparison BoltDB vs. HBase vs. Pinecone vs. RocksDB vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Wide-column store based on Apache Hadoop and on concepts of BigTable

A managed, cloud-native vector database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

github.com/boltdb/bolt

Technical documentation

hbase.apache.org/book.html

docs.pinecone.io/docs/overview

github.com/facebook/rocksdb/wiki

www.ultipa.com/document

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Pinecone Systems, Inc

Facebook, Inc.

Ultipa

Initial release

2013

2008

2019

2013

2019

Current release

2.3.4, January 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache version 2

commercial

Open Source

BSD

commercial

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

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

hosted

Linux

Data scheme

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

String, Number, Boolean

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

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

C++ API
Java API

RESTful HTTP API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Python

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Single row ACID (across millions of columns)

yes

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

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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.