DBMS > AnzoGraph DB vs. Couchbase vs. Quasardb vs. QuestDB

System Properties Comparison AnzoGraph DB vs. Couchbase vs. Quasardb vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Distributed, high-performance timeseries database

A high performance open source SQL database for time series data

Primary database model

Graph DBMS
RDF store

Document store

Time Series 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

Relational DBMS

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

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Website

cambridgesemantics.com/anzograph

www.couchbase.com

quasar.ai

questdb.io

Technical documentation

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

docs.couchbase.com

doc.quasar.ai/master

questdb.io/docs

Developer

Cambridge Semantics

Couchbase, Inc.

quasardb

QuestDB Technology Inc

Initial release

2018

2011

2009

2014

Current release

2.3, January 2021

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

3.14.1, January 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

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

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache 2.0

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

C, C++, Go and Erlang

C++

Java (Zero-GC), C++, Rust

Server operating systems

Linux

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

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

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

SQL-like query language

SQL with time-series extensions

APIs and other access methods

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

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

HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

C++
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

user defined functions and aggregates

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

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Automatic Sharding

Sharding

consistent hashing

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication with selectable replication factor

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

Transient mode

yes

through memory mapped files

User concepts

Access control

Access rights for users and roles

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

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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