DBMS > AlaSQL vs. Couchbase vs. QuestDB vs. TigerGraph vs. TimesTen

System Properties Comparison AlaSQL vs. Couchbase vs. QuestDB vs. TigerGraph vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A high performance open source SQL database for time series data

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

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

Relational DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

github.com/AlaSQL/alasql

docs.couchbase.com

questdb.io/docs

docs.tigergraph.com

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Couchbase, Inc.

QuestDB Technology Inc

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2011

2014

2017

1998

Current release

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

Release 22.1

License

Commercial or Open Source

Open Source

MIT-License

Open Source

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

Open Source

Apache 2.0

commercial

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 (Zero-GC), C++, Rust

C++

Server operating systems

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

Linux
OS X
Windows

Linux
macOS
Windows

Linux

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

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.

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

SQL with time-series extensions

SQL-like query language (GSQL)

yes

APIs and other access methods

JavaScript API

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

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

JavaScript

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

over HTTP

C++
Java

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

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

yes

PL/SQL

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

horizontal partitioning (by timestamps)

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication with eventual consistency

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships 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

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Ephemeral buckets

yes

through memory mapped files

yes

User concepts

Access control

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

Role-based access control

fine grained access rights according to SQL-standard

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