DBMS > Google Cloud Bigtable vs. Hypertable vs. Ignite vs. OpenSearch vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. Hypertable vs. Ignite vs. OpenSearch vs. XTDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

An open source BigTable implementation based on distributed file systems such as Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

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

Primary database model

Key-value store
Wide column store

Wide column store

Key-value store
Relational DBMS

Search engine

Document store

Secondary database models

Vector DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cloud.google.com/bigtable

ignite.apache.org

github.com/opensearch-project
opensearch.org

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

Technical documentation

cloud.google.com/bigtable/docs

apacheignite.readme.io/docs

opensearch.org/docs/latest

www.xtdb.com/docs

Developer

Google

Hypertable Inc.

Apache Software Foundation

Amazon Web Services

Juxt Ltd.

Initial release

2015

2009

2015

2021

2019

Current release

0.9.8.11, March 2016

Apache Ignite 2.6

2.5.0, January 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java, .Net

Java

Clojure

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Solaris
Windows

All OS with a Java VM

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

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

restricted

only exact value or prefix value scans

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

C++ API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Clojure
Java

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

Triggers

yes (cache interceptors and events)

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor on file system level

yes (replicated cache)

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

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.

yes

User concepts

Access control

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

Security Hooks for custom implementations

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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