DBMS > AlaSQL vs. AnzoGraph DB vs. Apache Drill vs. Couchbase vs. H2

System Properties Comparison AlaSQL vs. AnzoGraph DB vs. Apache Drill vs. Couchbase vs. H2

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Document store
Relational DBMS

Graph DBMS
RDF store

Document store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

alasql.org

cambridgesemantics.com/anzograph

drill.apache.org

www.couchbase.com

www.h2database.com

Technical documentation

github.com/AlaSQL/alasql

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

drill.apache.org/docs

docs.couchbase.com

www.h2database.com/html/main.html

Developer

Andrey Gershun & Mathias R. Wulff

Cambridge Semantics

Apache Software Foundation

Couchbase, Inc.

Thomas Mueller

Initial release

2014

2018

2012

2011

2005

Current release

2.3, January 2021

1.20.3, January 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

2.2.220, July 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

free trial version available

Open Source

Apache Version 2

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C, C++, Go and Erlang

Java

Server operating systems

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

Linux

Linux
OS X
Windows

All OS with a Java VM

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

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

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL SELECT statement is SQL:2003 compliant

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

JavaScript API

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC

Supported programming languages

JavaScript

C++
Java
Python

C++

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Java Stored Procedures and User-Defined Functions

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

Automatic Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication in MPP-Cluster

Multi-source replication

including cross data center replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency in MPP-Cluster

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

yes

Ephemeral buckets

yes

User concepts

Access control

Access rights for users and roles

Depending on the underlying data source

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

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