DBMS > Google Cloud Bigtable vs. RocksDB vs. Sphinx vs. TypeDB vs. Vertica

System Properties Comparison Google Cloud Bigtable vs. RocksDB vs. Sphinx vs. TypeDB vs. Vertica

Editorial information provided by DB-Engines

Name

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.

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

Open source search engine for searching in data from different sources, e.g. relational databases

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Key-value store
Wide column store

Key-value store

Search engine

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series 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	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

cloud.google.com/bigtable

Technical documentation

cloud.google.com/bigtable/docs

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

typedb.com/docs

vertica.com/documentation

Developer

Google

Facebook, Inc.

Sphinx Technologies Inc.

Vaticle

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

2013

2001

2016

2005

Current release

8.11.4, April 2024

3.5.1, February 2023

2.26.3, January 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

GPL version 2, commercial licence available

Open Source

GPL Version 3, commercial licenses available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

full-text index on all search fields

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language (SphinxQL)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

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

C++ API
Java API

Proprietary protocol

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

by using Cassandra

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

none

Multi-source replication

by using Cassandra

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Bi-directional Spark integration

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

substituted by the relationship feature

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

The original contents of fields are not stored in the Sphinx index.

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)

yes

at REST API level; other APIs in progress

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

Cost-based models and subscription-based models are both available. One license is...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.