DBMS > AlaSQL vs. CrateDB vs. Graph Engine vs. GridDB

System Properties Comparison AlaSQL vs. CrateDB vs. Graph Engine vs. GridDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Distributed Database based on Lucene

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Scalable in-memory time series database optimized for IoT and Big Data

Primary database model

Document store
Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

Key-value store
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	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

cratedb.com/docs

www.graphengine.io/docs/manual

docs.griddb.net

Developer

Andrey Gershun & Mathias R. Wulff

Crate

Microsoft

Toshiba Corporation

Initial release

2014

2013

2010

2013

Current release

5.8.1, August 2024

5.1, August 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

MIT License

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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

Java

.NET and C

C++

Server operating systems

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

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

.NET

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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.

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Supported programming languages

JavaScript

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
C++
F#
Visual Basic

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Configurable replication on table/partition-level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Read-after-write consistency on record level

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

rights management via user accounts

Access rights for users can be defined per database

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