DBMS > BoltDB vs. CockroachDB vs. KeyDB vs. Microsoft SQL Server vs. Titan

System Properties Comparison BoltDB vs. CockroachDB vs. KeyDB vs. Microsoft SQL Server vs. Titan

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

An embedded key-value store for Go.

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Microsofts flagship relational DBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.70
Rank	#225	Overall
	#31	Key-value stores

Score	4.74
Rank	#67	Overall
	#36	Relational DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

github.com/boltdb/bolt

www.cockroachlabs.com

github.com/Snapchat/KeyDB
keydb.dev

www.microsoft.com/en-us/sql-server

github.com/thinkaurelius/titan

Technical documentation

www.cockroachlabs.com/docs

docs.keydb.dev

learn.microsoft.com/en-US/sql/sql-server

github.com/thinkaurelius/titan/wiki

Developer

Cockroach Labs

EQ Alpha Technology Ltd.

Microsoft

Aurelius, owned by DataStax

Initial release

2013

2015

2019

1989

2012

Current release

24.1.0, May 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0, commercial license available

Open Source

BSD-3

commercial

restricted free version is available

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

yes

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Clojure
Java
Python

Server-side scripts

Stored procedures

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

yes

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

none

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

yes

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

simple password-based access control and ACL

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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