DBMS > AllegroGraph vs. RocksDB vs. Solr vs. Teradata

System Properties Comparison AllegroGraph vs. RocksDB vs. Solr vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

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

A widely used distributed, scalable search engine based on Apache Lucene

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Key-value store

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

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

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

docs.teradata.com

Developer

Franz Inc.

Facebook, Inc.

Apache Software Foundation

Teradata

Initial release

2004

2013

2006

1984

Current release

8.0, December 2023

8.11.4, April 2024

9.6.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

BSD

Open Source

Apache Version 2

commercial

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

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

hosted
Linux

Data scheme

yes

RDF schemas

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

bulk load of XML files possible

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SPARQL is used as query language

Solr Parallel SQL Interface

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API
SPARQL

C++ API
Java API

Java API
RESTful HTTP/JSON API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Java plugins

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

horizontal partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

optimistic locking

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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