DBMS > AnzoGraph DB vs. Lovefield vs. SiriDB vs. Solr vs. Transwarp Hippo

System Properties Comparison AnzoGraph DB vs. Lovefield vs. SiriDB vs. Solr vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Embeddable relational database for web apps written in pure JavaScript

Open Source Time Series DBMS

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

cambridgesemantics.com/anzograph

google.github.io/lovefield

siridb.com

solr.apache.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.siridb.com

solr.apache.org/resources.html

Developer

Cambridge Semantics

Google

Cesbit

Apache Software Foundation

Initial release

2018

2014

2017

2006

2023

Current release

2.3, January 2021

2.1.12, February 2017

9.6.1, May 2024

1.0, May 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

MIT License

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

JavaScript

Java

C++

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

All OS with a Java VM

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

Linux
macOS

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

Typing

predefined data types such as float or date

yes

Numeric data

yes

supports customizable data types and automatic typing

Vector, Numeric and String

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

All search fields are automatically indexed

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

via JavaScript builder pattern

Solr Parallel SQL Interface

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

HTTP API

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C++
Java
Python

JavaScript

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

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

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Java plugins

Triggers

Using read-only observers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users and roles

simple rights management via user accounts

yes

Role based access control and fine grained access rights

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Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
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AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

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