DBMS > Apache Hive vs. Google Cloud Datastore vs. XTDB

System Properties Comparison Apache Hive vs. Google Cloud Datastore vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store

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Score	75.77
Rank	#16	Overall
	#11	Relational DBMS

Score	3.62
Rank	#71	Overall
	#12	Document stores

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

hive.apache.org

cloud.google.com/datastore

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

cloud.google.com/datastore/docs

www.xtdb.com/docs

Developer

Apache Software Foundation

initially developed by Facebook

Google

Juxt Ltd.

Initial release

2012

2008

2019

Current release

3.1.3, April 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

MIT License

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

Clojure

Server operating systems

All OS with a Java VM

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

yes, extensible-data-notation format

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

SQL-like DML and DDL statements

SQL-like query language (GQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
Thrift

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

C++
Java
PHP
Python

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using Paxos

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Access rights for users, groups and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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