DBMS > EXASOL vs. Google Cloud Bigtable vs. HugeGraph vs. Lovefield

System Properties Comparison EXASOL vs. Google Cloud Bigtable vs. HugeGraph vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Key-value store
Wide column store

Graph DBMS

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

www.exasol.com

cloud.google.com/bigtable

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

Technical documentation

www.exasol.com/resources

cloud.google.com/bigtable/docs

hugegraph.apache.org/docs

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

Developer

Exasol

Google

Baidu

Google

Initial release

2000

2015

2018

2014

Current release

0.9

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 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

Java

JavaScript

Server operating systems

hosted

Linux
macOS
Unix

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Java
Lua
Python
R

C#
C++
Go
Java
JavaScript (Node.js)
Python

Groovy
Java
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

depending on used storage backend, e.g. Cassandra and HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Atomic single-row operations

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

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, groups and roles according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users, roles and permissions

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