DBMS > AnzoGraph DB vs. Databricks vs. Lovefield vs. SpaceTime

System Properties Comparison AnzoGraph DB vs. Databricks vs. Lovefield vs. SpaceTime

Please select another system to include it in the comparison.

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Embeddable relational database for web apps written in pure JavaScript

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Graph DBMS
RDF store

Document store
Relational DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Relational 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	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

cambridgesemantics.com/anzograph

www.databricks.com

google.github.io/lovefield

www.mireo.com/spacetime

Technical documentation

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

docs.databricks.com

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

Developer

Cambridge Semantics

Databricks

Google

Mireo

Initial release

2018

2013

2014

2020

Current release

2.3, January 2021

2.1.12, February 2017

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Apache 2.0

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

JavaScript

C++

Server operating systems

Linux

hosted

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

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

with Databricks SQL

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C++
Java
Python

Python
R
Scala

JavaScript

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

none

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

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

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

User concepts

Access control

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

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

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
19 June 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

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

provided by Google News

Databricks is Taking the Ultimate Risk of Building 'USB for AI' – AIM
15 June 2024, Analytics India Magazine

The Three Big Announcements by Databricks AI Team in June 2024
17 June 2024, MarkTechPost

Databricks launches LakeFlow to help its customers build their data pipelines
12 June 2024, TechCrunch

Databricks tells investors annualized revenue will reach $2.4 billion at midway point of year
13 June 2024, CNBC

Databricks open-sources Unity Catalog, challenging Snowflake on interoperability for data workloads
12 June 2024, VentureBeat

provided by Google News

Share this page