118 elements / The database universe
The periodic table of databases.
The 118 most popular databases. Familiar elements, a different kind of chemistry.
How to read the table
Each tile is one database. The number is its position in the DB-Engines popularity ranking for September 2026: element 1 is the most popular system in the world, element 118 the least popular of the top 118. The two-letter symbol is an editorial abbreviation, not an official one.
Color marks the database model each system is best known for: relational, document, key–value, wide column, search, time series, vector, or graph. Many databases support more than one model, so multi-model systems are placed by their leading model, and the detail view lists everything DB-Engines records. Positions follow the real periodic table, so ranks 57–71 and 89–103 sit in the two detached rows where the lanthanides and actinides go.
Popularity is not quality, performance, or market share. DB-Engines scores search interest, job postings, and developer discussion, and republishes the ranking monthly. This snapshot was taken on 2026-09-10.
Frequently asked questions
- What is the periodic table of databases?
- A visual index of the 118 most popular database management systems, arranged in the layout of the chemical periodic table. Each database's element number is its DB-Engines popularity rank, and its color is the database model it is best known for.
- Where does the ranking come from?
- From the DB-Engines Ranking, September 2026 edition. DB-Engines scores each system by search interest, job postings, professional-network mentions, and developer discussion, then publishes a new ranking every month.
- Why are ranks 57–71 and 89–103 in separate rows?
- Because the chemical periodic table puts the lanthanides (elements 57–71) and actinides (89–103) in two detached rows beneath the main body. The database table keeps the same shape, so those ranks sit in the same place.
- How often is the table updated?
- DB-Engines republishes its ranking monthly, and the table is refreshed from new snapshots. Each database's detail view shows its previous-month rank, so you can see who moved.
- Which of these databases does Bytebase support?
- Bytebase supports the most widely used relational and NoSQL engines on the table, including PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, Snowflake, ClickHouse, Redis, MariaDB, TiDB, and Spanner. See supported databases
Databases by model
Relational52
Tables, SQL, and structured records
1 Oracle, 2 MySQL, 3 Microsoft SQL Server, 4 PostgreSQL, 6 Snowflake, 7 Databricks, 9 IBM Db2, 10 SQLite, 13 MariaDB, 15 Microsoft Azure SQL Database, 16 Apache Hive, 17 Microsoft Access, 19 Google BigQuery, 22 SAP HANA, 23 Teradata, 24 FileMaker, 25 SAP Adaptive Server, 26 ClickHouse, 27 PostGIS, 28 Apache Spark (SQL), 32 Microsoft Fabric, 34 Firebird, 35 Amazon Redshift, 36 Microsoft Azure Synapse Analytics, 39 Informix, 40 Apache Flink, 41 Apache Impala, 42 DuckDB, 43 H2, 44 Amazon Aurora, 50 Trino, 51 Vertica, 55 dBASE, 59 Presto, 60 Netezza, 64 Greenplum, 70 Oracle Essbase, 72 CockroachDB, 78 Alibaba Cloud PolarDB, 79 Interbase, 82 TiDB, 84 OpenEdge, 87 Microsoft Azure Data Explorer, 88 Ingres, 89 SingleStore, 91 Apache Derby, 93 Google Cloud Spanner, 94 SAP SQL Anywhere, 101 HyperSQL, 113 SAP IQ, 116 YugabyteDB, 118 OceanBase
Document16
Flexible, nested records
5 MongoDB, 31 Microsoft Azure Cosmos DB, 37 Firebase Realtime Database, 45 Couchbase, 48 Google Cloud Firestore, 58 Realm, 61 CouchDB, 74 Apache Jackrabbit, 75 MarkLogic, 80 Arango, 81 Google Cloud Datastore, 95 Adabas, 110 IBM Cloudant, 111 RavenDB, 112 Rockset, 115 RethinkDB
Key–value13
Direct lookups by key
8 Redis, 18 Amazon DynamoDB, 38 Memcached, 52 etcd, 68 Hazelcast, 73 Aerospike, 76 RocksDB, 77 Oracle NoSQL, 86 Riak KV, 97 Apache Ignite, 99 Ehcache, 102 Valkey, 103 GemFire
Wide column7
Data organized in column families
12 Apache Cassandra, 33 Apache HBase, 65 ScyllaDB, 83 Datastax Enterprise, 100 Microsoft Azure Table Storage, 104 Apache Accumulo, 105 Google Cloud Bigtable
Search engine8
Indexing and information retrieval
11 Elasticsearch, 14 Splunk, 21 Apache Solr, 30 OpenSearch, 56 Algolia, 57 Microsoft Azure AI Search, 62 Sphinx, 114 Coveo
Time series10
Measurements over time
29 InfluxDB, 47 Prometheus, 49 Kdb, 63 TimescaleDB, 66 DolphinDB, 69 Apache Druid, 71 Graphite, 85 QuestDB, 90 TDengine, 96 Apache IoTDB
Vector5
Similarity and semantic retrieval
46 Pinecone, 53 Milvus, 54 Qdrant, 67 Weaviate, 92 Chroma
Graph7
Connected data, relationships, and RDF triples
20 Neo4j, 98 Amazon Neptune, 106 OrientDB, 107 Apache Jena - TDB, 108 GraphDB, 109 Virtuoso, 117 Stardog