DBMS > Drizzle vs. Google Cloud Bigtable vs. HugeGraph vs. Memgraph vs. RocksDB

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. HugeGraph vs. Memgraph vs. RocksDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

An open source graph database built for real-time streaming and compatible with Neo4j

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

Primary database model

Relational DBMS

Key-value store
Wide column store

Graph DBMS

Key-value store

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

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

Website

cloud.google.com/bigtable

github.com/hugegraph
hugegraph.apache.org

memgraph.com

rocksdb.org

Technical documentation

cloud.google.com/bigtable/docs

hugegraph.apache.org/docs

memgraph.com/docs

github.com/facebook/rocksdb/wiki

Social network pages

Developer

Drizzle project, originally started by Brian Aker

Google

Baidu

Memgraph Ltd

Facebook, Inc.

Initial release

2008

2015

2018

2017

2013

Current release

7.2.4, September 2012

0.9

8.11.4, April 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C and C++

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
macOS
Unix

Linux

Data scheme

yes

schema-free

yes

schema-free and schema-optional

schema-free

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

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

JDBC

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

Java API
RESTful HTTP API
TinkerPop Gremlin

Bolt protocol
Cypher query language

C++ API
Java API

Supported programming languages

C
C++
Java
PHP

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

Groovy
Java
Python

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

dynamic graph partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

yes

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

Multi-source replication using RAFT

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

relationships in graphs

Transaction concepts

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

ACID

Atomic single-row operations

ACID

with snapshot isolation

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

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Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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