DBMS > Google BigQuery vs. Graphite vs. JanusGraph vs. TypeDB vs. Warp 10

System Properties Comparison Google BigQuery vs. Graphite vs. JanusGraph vs. TypeDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

cloud.google.com/bigquery

github.com/graphite-project/graphite-web

janusgraph.org

typedb.com

www.warp10.io

Technical documentation

cloud.google.com/bigquery/docs

graphite.readthedocs.io

docs.janusgraph.org

typedb.com/docs

www.warp10.io/content/02_Getting_started

Developer

Google

Chris Davis

Linux Foundation; originally developed as Titan by Aurelius

Vaticle

SenX

Initial release

2010

2006

2017

2016

2015

Current release

0.6.3, February 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses available

Open Source

Apache License 2.0

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

Python

Java

Server operating systems

hosted

Linux
Unix

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API
Sockets

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript (Node.js)
Python

Clojure
Java
Python

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

by using Cassandra

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

by using Cassandra

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Relationships in graphs

substituted by the relationship feature

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

User authentification and security via Rexster Graph Server

yes

at REST API level; other APIs in progress

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

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Competitive advantages

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
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Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
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