DBMS > Drizzle vs. Google BigQuery vs. LevelDB vs. Memgraph vs. Netezza

System Properties Comparison Drizzle vs. Google BigQuery vs. LevelDB vs. Memgraph vs. Netezza

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.

Large scale data warehouse service with append-only tables

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

cloud.google.com/bigquery

github.com/google/leveldb

memgraph.com

www.ibm.com/products/netezza

Technical documentation

cloud.google.com/bigquery/docs

github.com/google/leveldb/blob/main/doc/index.md

memgraph.com/docs

Social network pages

Developer

Drizzle project, originally started by Brian Aker

Google

Memgraph Ltd

IBM

Initial release

2008

2010

2011

2017

2000

Current release

7.2.4, September 2012

1.23, February 2021

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

BSD

Open Source

BSL 1.1; commercial license for enterprise edition available

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

C++

C and C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Illumos
Linux
OS X
Windows

Linux

included in appliance

Data scheme

yes

schema-free

schema-free and schema-optional

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

Bolt protocol
Cypher query language

JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

dynamic graph partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication using RAFT

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Google Cloud Identity & Access Management (IAM)

Users, roles and permissions

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

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