DBMS > Google Cloud Bigtable vs. Hypertable vs. RocksDB vs. TerminusDB vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. Hypertable vs. RocksDB vs. TerminusDB 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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Primary database model

Key-value store
Wide column store

Secondary database models

Document store
RDF store

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

cloud.google.com/bigtable

rocksdb.org

terminusdb.com

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

Technical documentation

cloud.google.com/bigtable/docs

github.com/facebook/rocksdb/wiki

terminusdb.github.io/terminusdb/#

www.xtdb.com/docs

Developer

Google

Hypertable Inc.

Facebook, Inc.

DataChemist Ltd.

Juxt Ltd.

Initial release

2015

2009

2013

2018

2019

Current release

0.9.8.11, March 2016

9.2.1, May 2024

11.0.0, January 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

BSD

Open Source

GPL V3

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++

Prolog, Rust

Clojure

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

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

Data scheme

schema-free

yes

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.

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language (WOQL)

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

C++ API
Java API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP REST
JDBC

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

JavaScript
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Graph Partitioning

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

Journaling Streams

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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)

Role-based access control

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