DBMS > Apache Drill vs. Google BigQuery vs. HEAVY.AI vs. Hypertable vs. Memgraph

System Properties Comparison Apache Drill vs. Google BigQuery vs. HEAVY.AI vs. Hypertable vs. Memgraph

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Website

drill.apache.org

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

memgraph.com

Technical documentation

drill.apache.org/docs

cloud.google.com/bigquery/docs

docs.heavy.ai

memgraph.com/docs

Social network pages

Developer

Apache Software Foundation

Google

HEAVY.AI, Inc.

Hypertable Inc.

Memgraph Ltd

Initial release

2012

2010

2016

2009

2017

Current release

1.20.3, January 2023

5.10, January 2022

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

GNU version 3. Commercial license available

Open Source

BSL 1.1; commercial license for enterprise edition available

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++ and CUDA

C++

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

yes

schema-free

schema-free and schema-optional

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

C++ API
Thrift

Bolt protocol
Cypher query language

Supported programming languages

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Sharding

dynamic graph partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor on file system level

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

Depending on the underlying data source

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Users, roles and permissions

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

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