DBMS > Apache Pinot vs. Blazegraph vs. Couchbase vs. Percona Server for MongoDB vs. SWC-DB

System Properties Comparison Apache Pinot vs. Blazegraph vs. Couchbase vs. Percona Server for MongoDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

pinot.apache.org

blazegraph.com

www.couchbase.com

www.percona.com/mongodb/software/percona-server-for-mongodb

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.pinot.apache.org

wiki.blazegraph.com

docs.couchbase.com

docs.percona.com/percona-distribution-for-mongodb

Developer

Apache Software Foundation and contributors

Blazegraph

Couchbase, Inc.

Percona

Alex Kashirin

Initial release

2015

2006

2011

2015

2020

Current release

1.0.0, September 2023

2.1.5, March 2019

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.4.10-2.10, November 2017

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

extended commercial license available

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GPL Version 2

Open Source

GPL 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, C++, Go and Erlang

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

SQL-like query language

SPARQL is used as query language

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language

APIs and other access methods

JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

proprietary protocol using JSON

Proprietary protocol
Thrift

Supported programming languages

Go
Java
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C++

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

JavaScript

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Automatic Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

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

Ephemeral buckets

yes

via In-Memory Engine

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users and roles

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