DBMS > Google Cloud Bigtable vs. HBase vs. SQLite vs. Titan vs. VictoriaMetrics

System Properties Comparison Google Cloud Bigtable vs. HBase vs. SQLite vs. Titan vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used embeddable, in-process RDBMS

Titan is a Graph DBMS optimized for distributed clusters.

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Key-value store
Wide column store

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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

cloud.google.com/bigtable

hbase.apache.org

www.sqlite.org

github.com/thinkaurelius/titan

victoriametrics.com

Technical documentation

cloud.google.com/bigtable/docs

hbase.apache.org/book.html

www.sqlite.org/docs.html

github.com/thinkaurelius/titan/wiki

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Google

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Dwayne Richard Hipp

Aurelius, owned by DataStax

VictoriaMetrics

Initial release

2015

2008

2000

2012

2018

Current release

2.3.4, January 2021

3.45.3 (15 April 2024), April 2024

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Public Domain

Open Source

Apache license, version 2.0

Open Source

Apache Version 2.0

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

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

server-less

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

schema-free, schema definition possible

yes

dynamic column types

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

APIs and other access methods

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

Java API
RESTful HTTP API
Thrift

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

none

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

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 or Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

Atomic single-row operations

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

User authentification and security via Rexster Graph Server

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