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DBMS > LevelDB vs. Tarantool vs. Teradata Aster vs. TigerGraph

System Properties Comparison LevelDB vs. Tarantool vs. Teradata Aster vs. TigerGraph

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Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonTarantool  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTigerGraph  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsPlatform for big data analytics on multistructured data sources and typesA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMS
Relational DBMSGraph DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#115  Overall
#19  Key-value stores
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websitegithub.com/­google/­leveldbwww.tarantool.iowww.tigergraph.com
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.tarantool.io/­en/­docdocs.tigergraph.com
DeveloperGoogleVKTeradata
Initial release2011200820052017
Current release1.23, February 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoBSDOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++
Server operating systemsIllumos
Linux
OS X
Windows
BSD
Linux
macOS
LinuxLinux
Data schemeschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or datenostring, double, decimal, uuid, integer, blob, boolean, datetimeyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes infoin Aster File Storeno
Secondary indexesnoyesyes
SQL infoSupport of SQLnoFull-featured ANSI SQL supportyesSQL-like query language (GSQL)
APIs and other access methodsOpen binary protocolADO.NET
JDBC
ODBC
OLE DB
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Java
Python
R
C++
Java
Server-side scripts infoStored proceduresnoLua, C and SQL stored proceduresR packagesyes
Triggersnoyes, before/after data modification events, on replication events, client session eventsnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoSQL Map-Reduce Frameworkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyes, write ahead loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, full featured in-memory storage engine with persistencenono
User concepts infoAccess controlnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standardRole-based access control

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More resources
LevelDBTarantoolTeradata AsterTigerGraph
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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