DBMS > CrateDB vs. Galaxybase vs. Microsoft Azure Synapse Analytics

System Properties Comparison CrateDB vs. Galaxybase vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Scalable, ACID-compliant native distributed parallel graph platform

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.66
Rank	#223	Overall
	#37	Document stores
	#5	Spatial DBMS
	#17	Search engines
	#19	Time Series DBMS
	#15	Vector DBMS

Score	0.00
Rank	#394	Overall
	#42	Graph DBMS

Score	14.19
Rank	#38	Overall
	#23	Relational DBMS

Website

cratedb.com

galaxybase.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

cratedb.com/docs

docs.microsoft.com/azure/synapse-analytics

Developer

Crate

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Microsoft

Initial release

2013

2017

2016

Current release

5.8.1, August 2024

Nov 20, November 2021

License

Commercial or Open Source

Open Source

commercial

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

Java

C and Java

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

hosted

Data scheme

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

Strong typed schema

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

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

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

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

.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

Go
Java
Python

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined procedures and functions

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Role-based access control

yes

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More resources

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