DBMS > Brytlyt vs. Google Cloud Spanner vs. InfluxDB vs. RocksDB vs. TerarkDB

System Properties Comparison Brytlyt vs. Google Cloud Spanner vs. InfluxDB vs. RocksDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

DBMS for storing time series, events and metrics

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

brytlyt.io

cloud.google.com/spanner

www.influxdata.com/products/influxdb-overview

rocksdb.org

github.com/bytedance/terarkdb

Technical documentation

docs.brytlyt.io

cloud.google.com/spanner/docs

docs.influxdata.com/influxdb

github.com/facebook/rocksdb/wiki

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Brytlyt

Google

Facebook, Inc.

ByteDance, originally Terark

Initial release

2016

2017

2013

2016

Current release

5.0, August 2023

2.7.6, April 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

commercial

restricted open source version available

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

C, C++ and CUDA

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

through Homebrew

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
JSON over UDP

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

in enterprise version only

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

simple rights management via user accounts

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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