DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Blazegraph vs. Drizzle vs. InfinityDB vs. TerarkDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Blazegraph vs. Drizzle vs. InfinityDB vs. TerarkDB

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.

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A Java embedded Key-Value Store which extends the Java Map interface

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

blazegraph.com

boilerbay.com

github.com/bytedance/terarkdb

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

wiki.blazegraph.com

boilerbay.com/infinitydb/manual

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Blazegraph

Drizzle project, originally started by Brian Aker

Boiler Bay Inc.

ByteDance, originally Terark

Initial release

2016

2006

2008

2002

2016

Current release

2.1.5, March 2019

7.2.4, September 2012

4.0

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

GNU GPL

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

yes

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

SPARQL is used as query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

C++ API
Java API

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PHP

Java

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

fine grained access rights according to SQL-standard

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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